Abstract

The rationale for developing a theoretical model of computer-mediated communication (CMC) competence is established through review of social trends in the use of new media technologies. Special attention is paid to the role new media play in the formation and development of personal relationships. A model of CMC competence is then developed along the lines of motivation, knowledge, skills, context, and outcomes as a metaphorical typology for organizing existing CMC research. This research is reviewed as it informs, and is organized by, the model of CMC competence. A sampling of formal propositions resulting from the model is elaborated, and the results of preliminary pilot studies of the model are reviewed. The model is offered as a first step in examining individual differences in the domain of CMC relationships and media choice.

Introduction

Different media, which provide different sensory information, often produce different effects. Historically, every major innovation in communication technology has demonstrated a complex interplay with social forces to produce transformative effects on human relationships (Cheseboro, 2000; Cochrane, 1995; Inose & Pierce, 1984; Kedzie, 1997; McQuillen, 2003; Meyrowitz, 1985). Both the potential bright (utopian) and dark (dystopian) sides of such technological communications revolutions have been debated at length (e.g., Bargh, 2002; Gergen, 1991; Turkle, 1995), and the objective trends in social diffusion studied at length (e.g., Rideout, Roberts, & Foehr, 2005; U.S. Dept. of Commerce, 1998). If new technologies translate into new effects on society and human relationships, it follows that the competence with which any given person utilizes these new technologies is likely to affect whether this person views the technology as utopian or dystopian. This article formulates a theory of computer-mediated communication competence in an attempt to model skill with computer-based interpersonal communication.

At least two caveats to the transformative effects of communication technologies bear consideration. First, from a theoretical perspective, strong effects perspectives toward communication technologies have predominated. There is a tendency, especially in the early stages of theorizing that follow the diffusion of new technologies, to overattribute effects to technology and underattribute effects to the individual and social contexts. For example, early research tended to view mass communication messages as "magic bullets," unidirectionally producing strong effects in the form of persuasion. This paradigm gave way to a more moderated or interactionist paradigm, which recognized the importance of social and contextual forces in attenuating and accelerating the impact of mass communication. This interactionist paradigm is reflected more in current research trends in CMC (e.g., Hardy & Scheufele, 2005), although some anticipate a comeback by strong effects approaches (Herring, 2004).

The second caveat to the strong effects model of communication technology is that the complexity of technology and human relationships tends to require some degree of hindsight before even the right questions can be asked, much less the most accurate understandings formed (Herring, 2004). Such caveats have only recently begun framing the scholarly understanding of the Internet and its affiliated technological ancillaries (e.g., the world wide web, chat spaces, MUDs, MOOs, blogging, instant messaging or IM, videoconferencing, etc.). Collectively, these various uses of computer-mediated communication (CMC) are having transformative effects on human relations, but a full appreciation of the complexity of these effects remains elusive.

This analysis proffers a theory of computer-mediated communication competence to organize the accumulating scholarship on CMC. Before defining CMC competence, we identify some scope conditions. A theory of CMC competence does not directly compete with theories of media effects. For example, measures of CMC competence may provide useful dependent variables for models such as the social identification/deindividuation (SIDE) model (Lea & Spears, 1995; Spears, Postmes, Lea, & Wolbert, 2002), but competence itself is not intended to account for why CMC produces different communication effects from face-to-face (FtF) interaction. Likewise, a theory of CMC competence only partly overlaps with theories of how interaction differs based on the interaction medium. For example, hyperpersonal models (e.g., Walther, 1996) may claim that interaction will be differentially competent based on various parameters such as anticipated future interaction and task orientation, but these are not models of individual differences in competence given such parameters. A comprehensive theory of CMC interaction will eventually need to integrate models across such parameters.

CMC is tentatively defined as any human symbolic text-based interaction conducted or facilitated through digitally-based technologies. This working definition includes the Internet; cellular phone text, instant messaging (IM), and multi-user interactions (MUDs & MOOs); email and listserv interactions; and text-supplemented videoconferencing (e.g., decision support systems). This definition requires actual people engaged in a process of message interchange in which the medium of exchange at some point is computerized. There are some electronically enabled or enhanced, or otherwise mediated, forms of communication that might not qualify as CMC, including use of megaphones, hearing aids, or dedicated analog teletype systems. Furthermore, many media not ordinarily considered computers are included, as more and more media involve digital technologies. This definition intends to draw attention to the role of computer-assisted convergence in the technologically-mediated processes of communication.

The proposed theory is not strictly constrained to online interaction. Instead, it applies to any interpersonal communication process mediated through computer-assisted technologies. For example, when someone elects to IM rather than use vocalized phone or FtF interaction, this choice reflects a set of decisions about the functional value of that medium in that context. The cellular phone is a computer and will increasingly converge with all the various characteristics currently associated exclusively with computers. The cell phone also represents a set of technological constraints and affordances. Some of those constraints can be compensated for and others are more intractable. Consequently, this model is proposed to apply to all interactions that could be considered interpersonal computer-mediated interactions in which there are interdependent message response capabilities. To the extent that the Internet and websites provide a forum for email interaction, they could be within the scope of this model. However, the model is not intended to refer to specific hardware or software expertise, which tends to involve specialized forms of knowledge and skill.

The term text is not confined to linguistic symbols. Instead, it is defined broadly, consistent with cultural studies in which images, architecture, metaphors, and other message forms take on iconographic meaning. Specifically, text is defined as any message form to which patterned meanings are attributed. In this sense, sending advertisements or photographs through a cellular phone represents types of texts intended as messages. As technology converges and evolves, such definitions will also evolve. As technology increasingly permits virtual reality to approximate real life (RL), CMC will increasingly blur the notion of "text," perhaps to the point of dissolving its technological aspect entirely. Until then, the delimitation to text is a useful working space for analysis (Walther & Parks, 2002).

The Web and its Web of Relations

The geometry of CMC diffusion is astonishing by almost any standard of evaluation. Between 2000 and 2005 Internet usage grew an average of 160% worldwide—North America alone now has 68% of its population using the Internet, representing almost a quarter of worldwide usage (Internet World Stats, 2005). According to the Pew Internet and American Life Project (2000, hereafter "Pew"), every day close to 50 million Americans log onto the Internet, send or read email, and perform some activity on the World Wide Web. According to studies of U.S. youth, about half go online daily, about 85% live in homes with a computer, and one-third have used their cellular phones to send text messages (Lenhart, Madden, & Hitlin, 2005; Rideout et al., 2005). While diffusion is far lower in some other countries and cultures, the curve of diffusion is still steep (Cochrane, 1995; Kedzie, 1997). As technological distinctions dissolve between cell phones, television, and the computer, and as costs decrease, it seems inevitable that the reverberations of the communications revolution will be felt for some time into the future.

One of the most dramatic intersections of CMC and social contexts is in the arena of relationship initiation, maintenance, and dissolution. Until relatively recent times, CMC seemed to be viewed as text delivery media suited mostly to task-oriented applications (Garton & Wellman, 1995; Shields & Samarajiva, 1993; Sitkin, Sutcliffe, & Barrios-Choplin, 1992). People are increasingly integrating CMC into their repertoire of relationship development resources (Hovick, Meyers, & Timmerman, 2003; McCown, Fischer, Page, & Homant, 2001). "The Internet has come to rival the telephone as a medium for conducting personal relationships" (Baym, Zhang, & Lin, 2004, p. 306). Sizable proportions of CMC and Internet users yoke these technologies to relationship formation and development (see Table 1). Those who meet through CMC often make the transition to face-to-face or mixed media relationships (Cornwell & Lundgren, 2001; Cummings, Butler, & Kraut, 2002; McKenna, Green, & Gleason, 2002). As CMC diffusion increases, and as technological innovations enhance convenience, affordability, and applications, the value of CMC to relationship development is likely to increase.

Despite the relational uses of CMC, time invested online may in some way come at the expense of face-to-face (FtF) relationship contact or other important aspects of relationships, such as network size, density, or quality of interaction (Cai, 2004). One of the assumptions underlying this concern is that time spent on the Internet is time away from more social or "real" activities. "Almost two thirds of online teens (62%) think that the Internet does keep young people from doing more important things" (Pew, 2001, p. 31). Discontented youths appear to "spend more time using media than their most highly contented peers" (Rideout et al., 2005, p. 24). A study of chat room users found almost 32% "considered that use of the Internet interferes with other activities" (Peris et al., 2002, p. 47). The trade-off may also occur in certain types of relationships. For example, "64% of online teens say they think use of the Internet takes away from the time young people spend with their families" (Pew, 2001, p. 3). A corollary of this reasoning is that Internet use is positively related to loneliness and depression due to lack of more "social" forms or more "real" contact. Some research has shown slight but significant increases in loneliness and depression over time (Kraut et al., 1998), and decreases in social and familial involvement (Kraut et al., 1998; Nie & Erbring, 2000) with increasing Internet use. Many of these studies indicate that online interactions and relationships are in some significant way, "wanting" relative to more traditional media (Cummings et al., 2002).

These studies are far from uncontested. In the Nie and Erbring (2000) study, the vast majority of Internet users reported no effect of time online with time communicating with friends or family. The negative effects were concentrated among a small percentage of (problematic) users (Caplan, 2002; McKenna et al., 2002; Morahan-Martin & Schumacher, 2000), a finding supported by a Pew (2000) survey in which only 8% of Internet users reported they were socially isolated, although over twice as many nonusers (18%) reported they had "no one or hardly anyone to turn to" (p. 21). Furthermore, when Kraut et al. (2002) re-sampled the respondents from their original study three years later, they found that depression, which in the original study increased with increasing Internet use, actually significantly decreased with increasing Internet use, and loneliness no longer showed a significant association with increasing Internet use (see also Wästlund, Norlander, & Archer, 2001). Amichai-Hamburger and Ben-Artzi (2003) compared the Nie and Erbring hypothesis that Internet use leads to loneliness with the rival hypothesis that lonelier people are more likely to be drawn to use of the Internet, finding more support for the latter. This is consistent with research on Internet motives that found lonely users were generally more sociable online than offline (Morahan-Martin & Schumacher, 2003, p. 665).

The possibility exists that loneliness and depression are related to Internet and CMC use, but in complex ways. This possibility is suggested by a study that found email and Internet use were unrelated to depression at the bivariate level, but were predictive in a more complex path model (LaRose, Eastin, & Gregg, 2001). Other research indicates that the causal path may be reversed, suggesting that those who are lonely or socially anxious are particularly likely to use, and get the most out of, CMC interaction (cf., Patterson & Gojdycz, 2000). McKenna et al.'s (2002) path analysis showed social anxiety and loneliness facilitating expression of one's true self online, which predicted intimacy and the speed of developing intimacy, as well as the likelihood of using other modes of communication for relational contact. However, other research suggests that when lonely and socially anxious persons reach out through CMC, they engage people less likely to assuage such loneliness. Gross, Juvonen, and Gable (2002, p. 85) found that teenagers "who, on average, reported feeling more daily loneliness or social anxiety in school were more likely to communicate with a stranger than with a friend or close friend after school." Finally, based on a large representative sample, Wolak et al., (2002, p. 110) found that "a disproportionate number of adolescents with close online relationships were highly troubled, reported high amounts of conflict with their parents, low communication with parents and engaged in high levels of delinquency." It is unclear whether (a) these problems result from Internet use, (b) youths attempt to compensate for these problems by developing online relationships, or (c) there is a more complex interplay among these factors.

The preponderance of other simple survey research seems to indicate the net effect of the Internet and CMC technologies is, for the majority of users, to expand and enhance relationship networks, specific relational bonds, and, in many cases, the quality of relational interaction. In a separate study by Kraut et al. (2002), increasing use of the Internet correlated positively with indicators of social network size and familial involvement. In another survey, "59% of those who email family members report they communicate more often with significant family members now that they use email," "66% of Internet users say email has improved their connections with significant friends," and "60% of those who email friends report they communicate with significant friends more often now that they use email" (Pew, 2000, p. 7). In a later survey, "48% say their use of the Internet improves their relationship with friends; 32% say Internet tools help them make new friends" (Pew, 2001, p. 3). Rideout et al. (2005, p. 14) found that "those young people who spend the most time using media are also those whose lives are the most full with family, friends, sports, and other interests." At least a priori, then, the average person seems to view CMC as enabling or empowering in terms of relationship management, at least under certain strategic circumstances.

One theory in particular predicts CMC and "leaner" media actually facilitate development of intimacy because of their hyperpersonal affordances (e.g., Walther, 1996). McKenna et al. (2002) hypothesize that CMC creates greater intimacy because of its (1) anonymity, (2) lack of "gating" barriers (e.g., physical attraction cues), and (3) facilitation of locating those with shared interests. These features are predicted to increase self-disclosure and expression of true self. CMC interactions, compared to FtF interactions, appear to display greater self-disclosure and more depth and breadth of questions (Tidwell & Walther, 2002; Whitty, 2002). One survey found that about one-third of people believe it is easier to disclose "frank and unpleasant" things through email (Pew, 2000), which was generally viewed as an important benefit for openness in family and friend relationships.

It follows that "Internet relationships tend to develop closeness and intimacy more quickly than do real-life relationships" (McKenna et al., 2002, p. 20). Participants who interact via the Internet like one another more than those who interact FtF (Bargh, McKenna, & Fitzsimons, 2002). Other research showed that CMC interaction prior to FtF interaction increased enjoyment of the interaction (Dietz-Uhler & Bishop-Clark, 2001). McKenna et al. (2002) found that the relationship between liking and the processes of uncertainty reduction, depth, and breadth of disclosure was greater in CMC interactions than in FtF interactions (McKenna et al., 2002). Walther (1997) found group members given a longer-term identity perceived one another as more socially attractive than short-term identity members. Long-term members with group identity perceived one another as more physically attractive than short-term members with group identity, despite the fact they had never seen one another. Longer-term horizons of interaction apparently allow CMC to amplify social and relational interaction, especially when identification with the group as a whole rather than individual differences among members is salient. In contrast, Bertacco and Deponte (2005) found that the efficiency benefits of email relative to letter-writing tend to detract from the invocation of references to common relational ground (i.e., relationship memories), although egocentrism of messages did not differ across media.

Such hyperpersonal effects are likely to be affected by individual differences among users. For example, it is often stereotypically presumed "that people who enter cyberspace to form interpersonal relationships generally show greater difficulties in social face-to-face situations. They are considered shy and anxious people who have to hide behind a computer screen to be able to interact socially" (Peris et al., 2002, p. 44). It could be that lonely or socially anxious users may find FtF interaction too awkward for relationship initiation, and may benefit disproportionately from CMC (McKenna et al., 2002). Extroverts (Amichai-Hamburger & Ben-Artzi, 2003; Kraut et al., 2002; Mazur, Burns, & Emmers-Sommer, 2000; Wästlund et al., 2001; cf. Peris et al., 2002) and those who are particularly comfortable, confident, or expert in CMC use may disproportionately use or benefit from relational uses of CMC (see Campbell & Neer, 2001; Hacker & Steiner, 2001; Mazur et al., 2000; Tewksbury & Althaus, 2000; cf. Wright, 2000). So, for example, CMC efficacy appears to attenuate the link between CMC or Internet use and depression and loneliness (LaRose et al., 2001). People who are skeptical of CMC's capacity for facilitating relationships naturally appear to achieve less relationship development through CMC (Utz, 2000).

In summary, research demonstrates CMC has infiltrated, supplemented, and perhaps in some cases supplanted the arsenal of courtship and relationship pursuit, development, and management (Baym et al., 2004). CMC has become an important resource for developing and maintaining familial, friend, romantic, and coworker relationships (Lea & Spears, 1995). Therefore, a thorough understanding of CMC's role in relationship management becomes an important priority for scholarly agendas.

Toward a Model of CMC Competence

Theories and models are metaphors (Hawes, 1975; McQuail & Windahl, 1993). Theories and models serve as organizing devices for segmenting the symbolic realm of comprehension in a world that is potentially almost infinitely complex. The price paid in exclusion is ideally made up for through comprehension and research progress (Koutougos, 1989; Lakatos, 1970; Papineau, 1989). The metaphorical aspect of theories and models is all the more apparent in the social sciences, where symbolic practices and theorists self-reflectively comprise both object and observer (Ashmore, 1989). Models at moderate levels of abstraction may offer the most useful level (Turner, 1985, 1990) for organizing conceptions of CMC. Therefore, the value of a relatively comprehensive organizing scheme for the CMC literature is intended to outweigh the limitations imposed by its nascent status.

Previous research has tended to focus on the effects of CMC media, leading to the relative inattention to the social actor using the media. The theories that have been formulated thus far (see Walther & Parks, 2002) have tended to examine how CMC moderates such outcomes as impression formation (Hancock & Dunham, 2001; McKenna et al., 2002; O'Sullivan, 2000; Tanis & Postmes, 2003), impressions of appropriateness (Harper, 2002; Rice, 1993; Tidwell & Walther, 2002), effectiveness (Campbell & Neer, 2001; Tidwell & Walther, 2002), accuracy or coorientation (Kayany, Wotring, & Forrest, 1996; O'Sullivan, 2000), learning outcomes (Althaus, 1997; Brandon & Hollingshead, 1999; Hiltz, 1986), relationship intimacy (Parks & Floyd, 1996; Parks & Roberts, 1998; Tidwell & Walther, 2002), task-productivity or achievement (e.g., Burgoon et al., 2002; Hollingshead, McGrath, & O'Connor, 1993), and satisfaction (e.g., LaLomia & Sidowski, 1990). Other theories have focused more on the social actor's uses of CMC (e.g., Hunter & Allen, 1992; Markus, 1994; Perse & Ferguson, 2000). Still others have examined various individual differences that moderate CMC uses and outcomes (e.g., Kraut et al., 2002; Mazur et al., 2000). To date, however, there has been relatively little attempt to formulate an integrative theory of the social actor as he or she relates to, and through, CMC (cf. Hollingshead et al., 1993).

Borrowing from Goffman's dramaturgical perspective, Ring and colleagues (Ring, Braginsky, & Brajinsky, 1966; Ring, Brajinsky, Levine, & Braginsky, 1967; Ring & Wallston, 1968) suggested a dramaturgical metaphor for conceptualizing an interactant's (i.e., "actor's") performance quality. An actor needs to be motivated to give a good performance. Being motivated, however, is insufficient if the actor does not know the script which is to be enacted or the context in which the script is to be played out. Even motivation and knowledge are still insufficient unless actors have the acting skills requisite to translate their motivation and knowledge into competent action. This metaphor is mirrored in older metaphors of affective, cognitive, and behavioral factors of action (Havighurst, 1957). This metaphor was later imported as a way of organizing research on communication competence (see Rubin, 1983; Spitzberg, 1983; Spitzberg & Cupach, 1984) and elaborated to include the structure and expectancies comprising interaction contexts (Spitzberg & Brunner, 1991). These basic constructs, often expressed in different terminology, are reflected in current models of CMC processes (e.g., Ramirez, Walther, Burgoon, & Sunnafrank, 2002).

Motivation represents the energizing component of competent performance. Negative motivation is represented by constructs such as social anxiety, apprehension, shyness, and even apathy and disinterest. Positive motivation is reflected both by the antitheses of these constructs (e.g., confidence, comfort, communicator involvement, etc.), proactive CMC attitudes (Richter, Naumann, & Groeben, 2000), and by motivating forces such as goals, perceived benefits, motives, gratifications, and uses. Because motivation has both positive and negative facets, there is the possibility of ambivalence, in which the weight of one overpowers the other. Stage fright may disable an otherwise knowledgeable and skilled actor's performance, and even frightened actors sometimes manage their fears through sheer determination and skill.

Knowledge is represented primarily by cognitive characteristics reflecting such constructs as planning, uncertainty reduction, familiarity, expertise, and other indicators of comprehension. Knowledge can be highly compartmentalized (Smith, Caputi, Crittenden, Jayasuriya, & Rawstone, 1999; Smith, Caputi, & Rawstone, 2000) or a more general dimension of perceived ability (Potosky & Bobko, 1998). A person may know a lot about hardware and software, yet little or nothing about how to compose a message sensitive to status differential between sender and receiver. Knowledge can be operationalized through such constructs as self-monitoring, planning, cognitive complexity, and experience.

Skills are the repeatable, goal-oriented behavioral tactics and routines that people employ in the service of their motivation and knowledge. Spitzberg and Cupach (2002) identified over 100 distinct skills in the communication competence literatures. However, they also argued that these skills probably reflect a more parsimonious set of skill clusters and dimensions. Specifically, at the microscopic level, interpersonal skills reduce to four basic skill clusters: attentiveness (i.e., displaying concern for, interest in, and attention to the other person or persons in the interaction), composure (i.e., displaying assertiveness, confidence, being in control), coordination (i.e., displaying deft management of timing, initiation and closure of conversations, topic management, etc.), and expressiveness (i.e., displaying vividness and animation in verbal and nonverbal expression). This typology of skills has been confirmed in a variety of measurement studies (Spitzberg, 1994b; Spitzberg, Brookeshire, & Brunner, 1990).

It is axiomatic that communication competence is contextual (Spitzberg, 2000; Spitzberg & Cupach, 2002). However, surprisingly few studies have attempted to specify a theory of context (cf., Argyle, Furnham, & Graham, 1981; Heise, 1979). One of the reasons context has eluded theoretical specification is its complexity, which is illustrated by the manifold ways in which contexts have been conceptualized. Contexts vary by cultural, chronological, relational, environmental, and functional characteristics (Spitzberg, 2000; Spitzberg & Brunner, 1991). Each of these facets affects communication competence in complex ways, and any attempt to formulate a theory of competence that ignores these facets is necessarily incomplete.

The motivation, knowledge, and skills model has stimulated extensive conceptual (Spitzberg, 2000) and empirical (e.g., Spitzberg, 1990, 1991; Spitzberg & Brunner, 1991; Spitzberg & Cupach, 1984; Spitzberg & Hecht, 1984; Spitzberg & Hurt, 1987) work. The model organizes a vast expanse of research projects that otherwise would have no obvious connection, such as research on communication apprehension, goals, planning, cognitive complexity, and involvement. The model has also been extended to particular contexts such as the instructional (Spitzberg & Hurt, 1987) and intercultural (Spitzberg, 1994c). The applicability of the model to the CMC context, however, has only recently been examined (Bubaš, 2002, 2005; Bubaš & Aurer, 1998; Bubaš, Radošević, & Hutinski, 2003; Bunz, 2002; Harper, 1999; Morreale, Spitzberg, & Barge, 2001).

CMC Motivation

Motivation has been investigated in various guises in relation to CMC, although most typically it is viewed as a function of approach motives such as Internet affinity (Bubaš & Hutinski, 2003) or avoidance motives such as computer or information anxiety (Barbeite & Weiss, 2004; Beckers & Schmidt, 2001; Chua, Chen, & Wong, 1999; Gaudron & Vignoli, 2002; Wheeless, Eddleman-Spears, Magness, & Preiss, 2005). Motivation can be indexed positively by a range of constructs such as willingness to adopt new communication technologies, satisfaction, gratifications, and positive attitudes toward such technologies. Wright (2000) found online apprehension was unrelated to time online. Campbell and Neer (2001) found communication apprehension and interaction involvement predicted CMC style factors of openness and affability, although neither construct was related to perceived CMC effectiveness and satisfaction. In another study, computer anxiety was negatively related to WWW gratifications obtained (Tewksbury & Althaus, 2000). Mazur et al. (2000) found communication apprehension was positively related to relational interdependence via CMC, suggesting those who are too apprehensive to form FtF relationships rely on CMC as a medium of relational development. Several studies suggest that lonely or shy persons tend to seek social gratifications from CMC to compensate for their perceived isolation or anxieties (Gross et al., 2002; Knox et al., 2001; Morahan-Martin & Schumacher, 2000; Scharlott & Christ, 1995).

Regarding positive motivations, research shows "personal benefit" of CMC usage is predictive of frequency of use and satisfaction with email (Hunter & Allen, 1992) as well as problematic Internet uses (Caplan, 2002). Relative value of information contributed and technology-specific competence appear to increase a person's motivations to contribute to an organizational information commons (Fulk, Schmitz, & Steinfield, 1990; Yuan et al., 2005). Extroversion, a trait disposed toward communication, moderates the impact of CMC on loneliness and depression (Kraut et al., 2002; Mazur et al., 2000), and is positively related to amount of Internet usage (Wästlund et al., 2001). Hacker and Steiner (2001) found "comfort" with Internet usage correlated with actual usage. "Approach" and goal-oriented traits, such as expressive and instrumental dispositions, predict computer interest (Bozionelos, 2002), and the value of the medium in facilitating such information needs predicts web usage (Ambra & Rice, 2001). Utz (2000) found that whereas sociability was unrelated to relationship development via CMC, skepticism toward CMC as a mode of relationship formation was negatively related to relationship development through CMC. Gratifications, or benefits, sought through web use (e.g., pastime, entertainment, relaxation, escape, excitement, companionship) predict actual web use (Perse & Ferguson, 2000), although they may also represent the rationalized reasons for pathological use or Internet addiction (Morahan-Martin & Schumacher, 2000). Perse and Ferguson (2000) unexpectedly found computer access was negatively related to web use, suggesting motivation is necessary to stimulate actual utilization of CMC. However, Hacker and Steiner (2001) found that opportunities to use the Internet correlated significantly with usage.

Séguin-Levesque, Laliberté, Pelletier, Blanchard, and Vallerand (2003) are among the few to have formulated a dual motivation approach to Internet motivations. They distinguish between intrinsic motivations and extrinsic motivations. Intrinsic motives emerge from one's own values and self-concept, leading to freely chosen activity, which is labeled harmonious passion. Extrinsic motives emerge from participation in interesting activities that are inconsistent with self, leading to a sense of compulsion rather than freely chosen activity. These motives belong to a cluster of motives considered obsessive passion. Both motives were significantly correlated with hours per week on the Internet (.30, .33, p<.01, respectively), but only obsessive passion was positively correlated with relational conflict (r=.35, p<.01) and negatively correlated with relational satisfaction (r=-.30, p<.01).

Thus, although there are some obvious inconsistencies in the research record, there seems to be a broad cluster of motivational constructs suggesting the important role that motivation plays in predicting the use and success in using CMC technologies. CMC motivation is defined here as the ratio of approach to avoidance attitudes, beliefs, and values in a given CMC context.

CMC Knowledge

In general, it seems reasonable to expect that the more knowledgeable a person is with CMC, the more motivated the person will be to use CMC. Conversely, the more motivated someone is to use CMC, the more knowledgeable the person should become. Therefore, there is a feedback loop between these constructs, despite their distinct conceptual boundaries. CMC self-efficacy reflects this overlap. CMC self-efficacy is the belief in one's ability to use CMC effectively, although it has also been defined as an "expectation of mastery" (Beckers & Schmidt, 2001). Research shows Internet self-efficacy is predictive of Internet use, email use, and Internet experience (Eastin & LaRose, 2000; Fang, 1998; LaRose et al., 2001).

Another intersection of knowledge is with the multidimensional constructs of familiarity, expertise, use, and literacy (LaLomia & Sidowski, 1990; Smith et al., 1999; van den Hooff, Groot, & Jonge, 2005). As CMC technology use increases, the more knowledge and skills should increase. Knowledge consists of both content and procedural forms of knowledge (Greene, 1997). Content knowledge is an understanding of the "what" of communication: topics, rules, concepts, and so forth. Procedural knowledge is comprehension of the "how" of communication; how content knowledge can be applied. It is analogous to the difference between knowing the content of a joke versus knowing how to tell it. CMC use and experience, therefore, represent a confluence of both content and procedural knowledge as well as skills (Smith et al., 1999). It is not surprising, therefore, that computer use is positively related to Internet skill over time (Kraut et al., 2002). Hunter and Allen (1992) likewise found "ease of learning" was positively related to email satisfaction and usage frequency. Perse and Ferguson (2000) found computer expertise and experience predicted web use. Markey and Wells (2002) found that chat room experience predicted judges' liking of chatroom behavior.

Knowledge of CMC can also be obtained through the use of online information-seeking strategies (Ramirez et al., 2002). Such strategies represent a confluence of knowledge and skills, in that goal-oriented tactics are performed to acquire knowledge that will in turn facilitate knowledge and competence. In short, there is a complex of constructs that index knowledge of CMC that is likely to be a central component of competence in the computer-mediated domain of interaction. CMC knowledge is defined here as the cognitive comprehension of content and procedural processes involved in conducting appropriate and effective interaction in the computer-mediated context.

Conceptualizing CMC competence as a function of motivation and knowledge indicates that CMC motivation provides the impetus for more skilled CMC and that CMC knowledge provides the content and procedures for implementing these motives. Motivation and knowledge may at times be merely summative, but they may also interact in certain ways. That is, a person high in both may be significantly more competent than someone only moderate or low on one or the other. As such, these concepts lead to the following propositions:

1. CMC motivation is positively related to CMC knowledge.
   1. CMC anxiety is negatively related to CMC knowledge.
   2. CMC efficacy is positively related to CMC knowledge.
2. CMC motivation and knowledge provide unique and interactive effects in predicting CMC competence.

CMC Skills

Most theories of CMC are predicated on an assumption that media are structurally leaner than FtF interaction, and this relative poverty constrains expression of interpersonal skills (Cerulo, 1997; Sheehy, 1995). These theories vary in the degree to which users are expected to compensate for these constraints (Walther & Parks, 2002). Studies also sometimes predict that features of the medium enhance or exacerbate nonmediated interpersonal skills. For example, the triple A engine of Internet access, anonymity, and affordability (Cooper, 2000) are expected to facilitate Internet addiction, especially cybersex addiction (Brenner, 1997; Cooper, Delmonico, & Burg, 2000; Davis, 2001; Griffiths, 1999, 2001; McGrath & Casey, 2002; Morahan-Martin & Schumacher, 2000; Pratarelli, Browne, & Johnson, 1999; Schneider, 2000; Schwartz & Southern, 2000; Suler, 1999). Others have speculated that the leaner and relatively anonymous features of CMC lead to greater flaming, that is, greater expression of aggressiveness and hostility (Castellá, Abad, Alonso, & Silla, 2000; Markus, 1994; Spears et al., 2002), even if the overall prevalence of such flaming may be relatively low (Markus, 1994; Sheehan & Hoy, 1999). Other research suggests that fluency is disrupted by media such as videoconferencing (Straus, Miles, & Levesque, 2001).

If structural characteristics of the medium affect the expression of interpersonal skills, it is less understood if such skills are directly translatable to the CMC context (Hutchby, 2001). What is "listening" in regard to email? What is "talk time" in regard to email? Such questions suggest interpersonal skills may be transformed or irrelevant rather than merely moderated by CMC. However, Morreale et al. (2001) speculate that basic interpersonal skills are either directly translatable or have close analogues in the CMC context. Attentiveness, or other-orientation, reflects the extent to which interest, concern, and attention are shown to the other interactant(s).

Attentiveness can be displayed in CMC through a variety of tactics, including the degree to which topics initiated by others are taken up in one's own CMC message content, use and appropriateness of questions, social support and comforting sophistication of message content, and politeness and appropriateness of message content. Pratt, Wiseman, Cody, and Wendt (1999), for example, found interactants modulated the depth of their questions over the stages of the relationship in CMC interactions, suggesting a sensitivity to the appropriateness of interrogative strategies. Similarly, Bunz and Campbell (2004) found that responders to emails with politeness cues responded more politely, indicating an adaptation to the sender. CMC users also employ questions of greater depth than FtF interactants (Tidwell & Walther, 2002, p. 331), suggesting an adaptation to the medium. Rouse and Haas (2003) found that chatroom use of compliments correlated with observer-rated judgments of extraversion (r=.51, p<.01) and openness to experience (r=.42, p<.01) and conscientiousness (r=.24, p<.05).

Composure is displayed in CMC through avoiding cues of uncertainty such as the use of linguistic qualifiers in message content, the proportion of valenced opinion expression of message content, the use of directives and imperatives relative to inquiries or neutral language content, the use of compliance-gaining tactics, and perhaps task or topical redirection and topic initiations. Many linguistic indicators of gender and power are likely to reflect composure as well (e.g., Herring & Martinson, 2004). Assertiveness could also be viewed as a proxy for composure (see Castellá et al., 2000), presuming it is differentiated from aggressiveness.

Composure, which is more of a self-promotional skill, is likely to be delicately balanced in relation to attentiveness, which is more of an other-promotional skill. Such dialectical tensions do not necessarily represent fundamental incompatibilities (Spitzberg, 1993, 1994a). Yet, to date, there is relatively little research directly relevant to indices of composure in CMC interaction. Rouse and Haas (2003) coded the use of self-denigrating or self-depreciation comments in chat space (e.g., "I really suck at this game"), which might be a proxy, albeit a somewhat ambivalent one, for self-confidence. This behavior predicted judges' ratings of the communicator's extraversion (r=.53, p<.01) and openness to experience (r=.56, p<.01).

Coordination, or interaction management, skills can be displayed via CMC through the deft management of the number of messages, the length of messages, the rapidity of response to others' messages, and the content and task relevance of responses. Coordination is likely to be closely aligned with computer-email-web fluency (Bunz, 2004), and is similar to many of the process effects attributed to the interactivity of media, such as navigation control, pace control, rapidity, and responsiveness (Burgoon et al., 2000; Burgoon et al., 2002; Sohn & Lee, 2005). For example, rapidity of response predicts interpretation of affection depending on task versus socioemotional content and time of day that messages are sent (Walther & Tidwell, 1995). Rouse and Haas' (2003) study found the number of irrelevant comments made in chat space predicted judges' ratings of extraversion (r=.45, p<.01), openness to experience (r=.35, p<.01), and conscientiousness (r=.34, p<.01).

Expressiveness skills can be displayed in CMC interactions through the use of emoticons and similar paralinguistic features of message content, the use of humor, and even the depth and breadth of self-disclosure (Castellá et al., 2000; Whitty, 2003). For example, CMC users employ greater proportions of self-disclosure and questions than FtF interactants (Tidwell & Walther, 2002). Emoticons apparently attenuate the perceived hostility of mild-to-moderately antagonistic messages, but increase the perceived hostility of highly antagonistic messages (Thompson & Foulger, 1996). Flaming may reflect a dark side of expressiveness, as well as of attentiveness (O'Sullivan & Flanagin, 2003). The use of paralanguage is correlated to the amount of time spent engaging in MUD interactions, as well as the level of development of online friendships (Utz, 2000). In Rouse and Haas' (2003) study, the sheer number of contributions made in chat space predicted judges' ratings of extraversion (r=.57, p<.01) and openness to experience (r=.43, p<.01). Use of humor, another potential indicator of expressiveness, also predicted judges' ratings of neuroticism (r=.37, p<.01) and extraversion (r=.36, p<.01). A converse to expressiveness is lurking (Preece, Nonnecke, & Andrews, 2004), in which computer users enter a chat space and observe but do not participate.

In summary, it appears that skills in the nonmediated context are relatively translatable to the mediated context, allowing for certain structural constraints of the medium. Burgoon et al. (2002; Burgoon et al., 2000) argue that these constraints merely produce an upper boundary on the principle of interactivity, which further suggests the functional equivalence of FtF skills to the CMC context. Direct comparisons suggest that people find the perceived quality of Internet-based interaction lower than FtF or telephone interaction (Baym et al., 2004). Therefore, it becomes important to identify the skills entailed in compensating for media-based constraints. Extensive research indicates that four clusters represent a relatively comprehensive typology of FtF interpersonal skills: attentiveness, composure, coordination, and expressiveness (Spitzberg, 1994b; Spitzberg & Cupach, 2002).

If CMC competence, like FtF competence, is a function of attentiveness, composure, coordination, and expressiveness skills translated into the mediated context, then the following propositions extend from the motivation, knowledge, and skills model.

1. CMC motivation is positively related to CMC skills (i.e., attentiveness, composure, coordination, expressiveness).
2. CMC knowledge is positively related to CMC skills (i.e., attentiveness, composure, coordination, expressiveness).

CMC Context

Following the five typological facets of context identified by Spitzberg (2000; Spitzberg & Brunner, 1991), CMC interaction is expected to vary based on cultural, chronological, relational, environmental, and functional features. Culture consists of patterns of behavior, attitude, belief, value, and ritual transmittable across generations. These patterns coalesce in variables of nationality, ethnicity, race, religion, and gender, to name a few. While there has been little research on many of these comparative, inter-cultural, or cross-cultural foci (cf. Brosnan & Lee, 1998; Hart, 1998; Rice, D'Ambra & More, 1998; Rosen & Weil, 1995), at least one factor has stimulated its share of research: gender.

To the extent that gender is a complex set of culturally constructed behaviors and beliefs, it follows that gender may influence, and be influenced by, CMC (Herring, 2001). Surprisingly, research is actually mixed in relation to gender (e.g., Savicki, Kelley, & Oesterrich, 1999; Wachter, 1999; Wolak et al., 2002). For example, Herring and Martinson (2004) demonstrated that people do appear to have various gender schemata for "performing" gender online, but that people are no better than chance at accurately identifying the gender of online communicators. Studies have found relatively few differences by biological sex in forms of CMC usage such as amount of use or time online (see Goodson et al., 2001; Knox et al., 2001; Kraut et al., 1998; McKenna et al., 2002; Wästlund et al., 2001; Whitley, 1997; cf. Pew, 2000; Sussman & Tyson, 2000). However, functional applications of CMC may differ by sex. For example, Wolak et al. (2002) found girls were slightly more likely than boys to form online friendships and close relationships over the previous year (29 vs. 23%, 19% vs. 16%, respectively). McKenna et al. (2002) found females perceived their Internet-formed relationships as higher in intimacy than did males. Females appear more comfortable in CMC with other females (Corston & Colman, 1996). Whitty (2002) found women were more supportive and men more deceptive in chat spaces. In negotiation contexts, males appear to form more competitive relationships with males than with females (Thompson & Nadler, 2002). It appears that women recognize the "relational" value of CMC more so than men (Pew, 2000), and are more attuned to a concern for appropriateness in CMC message construction (Heerring, 2001).

The chronological facet of context has been studied in a wide variety of ways. At a very macro level, age and developmental changes reflect the influences of time within the individual, as well as cohort effects over time. Thus, for example, teenagers have been found to react to CMC usage somewhat differently from adults. Kraut et al. (2002) found that as Internet use increased, teenagers increased their available social support and family communication, whereas adults increased their FtF interactions with friends and family and their closeness with distant relatives. At the more micro level, the chronological dimension of CMC is concerned with the timing and sequencing of messages. For example, the medium selected for messages is likely to vary based on time pressure (Bertacco & Deponte, 2005; Sitkin et al., 1992; van den Hooff et al., 2005). Walther and Tidwell (2002) found time of day interacted with function (task vs. socioemotional) to influence the attributions people made to email messages. Walther, Anderson, and Park (1994) found that as the time constraint of the CMC interaction "relationship" increases, task orientation of the message exchanges tends to become more prominent, whereas more unrestricted time constraints, in which future relations are contemplated, produce more socio-emotional message exchanges and attraction. Walther (1997) found that short-term groups tended to view their communication as less intimate and less socially attractive than long-term groups. Hollingshead et al. (1993) found that differences between FtF and CMC tend to disappear over time as a group acclimates to the media, but these differences can be reintroduced as changes to the media or group are introduced.

The third facet of contexts is the type of relationship among interactants. One of the standard relational questions of CMC is whether such mediated relationships are somehow different qualitatively from "real life" (RL) relationships. Peris et al. (2002, p. 47) found that chat room users found their "friendly (70.6%) or romantic cyberrelations (55.6%) just as important as face-to-face relations." A survey by McKenna et al. (2002) found 84% of respondents "reported that their on-line relationships were as real, as important, and as close as their non-Internet relationships" (p. 22). Indeed, the Internet-formed relationships were as stable over a 2-year period as FtF relationships in comparable studies (McKenna et al., 2002, p. 22). Similarly, Parks and Floyd (1996) and Parks and Roberts (1998) found typical CMC based relationships showed consistent evidence of being above the midpoint of criteria of relationship development and intimacy. Another study found that people in both CMC and FtF relationships "perceived their relationships as satisfying and as offering opportunity for growth, but realspace respondents considered their relationships as more serious and they expressed greater commitment" (Cornwell & Lundren, 2001, p. 205). As CMC relationships evolve over time, attributional confidence regarding online relational partners approaches greater equivalence with FtF, although "CMC participants felt the setting impaired their ability to get to know their partner … more so than did FtF interactants" (Tidwell & Walther, 2002, p. 338). There is, as yet, relatively little research on how message content changes based on relationship other than the status of the sender relative to the recipient (Markus, 1994).

The physical environment, place, or situational facet of CMC interaction is, in a large part, instantiated by the features of the media themselves. O'Sullivan (2000) views the media of communication as a meta-communicative message in itself. That is, the computers are a prominent feature of the physical environment, as well as the physical constraints of the context. However, features of the media can change in important ways. For example, Burgoon et al. (2002) found proximal mediated contexts (i.e., interactants can see one another interacting on computers, but cannot read each others' screens while interacting) produce a greater sense of relational connection than nonproximal or distal mediated interactions. The "geographical reach" of the medium appears to influence the selection of email as a form of CMC (van den Hooff et al., 2005).

In the case of CMC, the aspects of the physical environment that have received the most attention are the interactivity of the technology. Most current theories concur on at least one central tenet, that the more interactive, rich, or adaptable a medium is, the more it should facilitate socioemotional, personal, complex, and subtle communication processes. Simple "mass communication media" such as listservs, standard websites, electronic bulletin boards, and so forth, are likely to be competent for simple information transfer. In such contexts, efficient media are likely to be preferred. Efficiency here would reflect time and effort required to compose and send messages relative to the number of recipients receiving the message. In contrast, messages calling for sensitivity to individual concerns are likely to be more competently delivered through media that better represent the breadth and depth of natural FtF interaction. As convergence increases, it seems likely that media will increasingly be adaptable to either mode of interaction (i.e., efficient and interactive on demand). Thus, text messaging increasingly can be directed interactively to a single person or mass mailed to distribution lists. Such adaptability of medium is likely to enhance the competent communicator's ability to adapt the medium to the context.

Another aspect of the physical context is geographic proximity. Some research suggests that communication technologies are used more to compensate for geographic distance in relationships (Baym et al., 2004). Burgoon et al. (2002) found proximal CMC forms of interaction were perceived as higher in perceived sociability, connectedness, and task attraction.

The final contextual facet is function. Conflicts are different contexts from get-acquainted conversations. Running a task-oriented CMC meeting is a different context from flirting on a computer dating service chat-space (Whitty, 2003). Many research findings are merely suggestive of such functional influences. For example, "compared to face-to-face negotiation, e-mail reduces rapport building" and "increases multi-issue offers" (Thompson & Nadler, 2002, p. 116). Interactants tend to select media in part on the basis of the function of the intended message (Kayany et al., 1996; Markus, 1994). Research on youth indicates that over three-fourths of their online interactions serve "social" functions (Baym et al., 2004). There is some evidence of greater flaming and hostility in mediated contexts than FtF interactions (Walther & Parks, 2002, p. 532), although this may depend in part on whether the relationship context is in-group or out-group (Thompson & Nadler, 2002), and the particular construction of the message (Thompson & Foulger, 1996). Finally, people apparently feel that they can reveal their more frank, unpleasant (Pew, 2000), or "true" selves (Bargh et al., 2002; McKenna et al., 2002), even if CMC tends to be more facilitative of task-oriented interaction than FtF interactions (Walther & Parks, 2002).

Thus far, there does not appear to be a theoretical model that would integrate all the various functions of messages via CMC any more than there is a comparable model for nonmediated interactions. Nevertheless, it seems clear that interaction in the service of different functions is likely to interact with the media of CMC in distinct ways, and that contextual function must be accounted for in any comprehensive theory.

There are at least five contextual facets of interaction, whether CMC or FtF. As such, it seems reasonable to extend the logic of the model thus far to propose that the more CMC skills are adapted to these contextual facets, the more competent the interaction will be.

1. Media Factor Propositions:
   1. Media interactivity is positively related to CMC competence for socioemotionally and relationally focused functions.
   2. Media efficiency is positively related to CMC competence for informationally focused functions.
   3. Media adaptability is positively related to CMC competence.
2. Message Factor Propositions:
   1. Congruence of message content and function with personal functional objective is positively related to CMC competence.
   2. Congruence of message task-orientation with contextual and media factors is positively related to CMC competence.
   3. Congruence of message openness with contextual and media factors is positively related to CMC competence.
3. The more CMC skills are adapted or sensitive to cultural, chronemic, relational, environmental, and functional co-interactant positive expectancies, the more competent the CMC interaction.

Outcomes

There are many possible outcomes of interaction (e.g., Ambra & Rice, 2001). Among the most common outcomes by which competence in CMC interaction can be assessed are the following: coorientation (understanding, accuracy, clarity), perceptions of appropriateness and effectiveness, efficiency, task success or accomplishment, satisfaction (Harrison & Rainer, 1996; Straus et al., 2001; Westmyer, DiCioccio, & Rubin, 1998), and relationship development (attraction, intimacy, commitment, etc.), as well as more context-specific outcomes such as network integration, learning, or symptom (e.g., depression, loneliness) relief (see Spitzberg, 2000; Spitzberg & Cupach, 2002).

Coorientation refers to the degree of correspondence between a sender's intentions and/or message content and the interpretations of the receiver(s). Appropriateness is the perceived legitimacy or fit of a message to the context. It is related but not isomorphic with conformity, because an interactant may negotiate new contextual rules in the process of violating existing rules. Effectiveness is the degree to which preferred objectives are optimized. It is related to but not isomorphic with satisfaction because an effective choice may be relative when there is no satisfactory response, in which case the least punishing response may be considered effective. Satisfaction is the positive affect associated with the fulfillment of positively valenced expectancies (Spitzberg & Hecht, 1984). Efficiency is the relative economy with which preferred outcomes are achieved. The less time, effort, or resources invested to achieve the same outcome, the more efficient the process. Finally, relational development represents the degree of breadth, depth, intimacy, closeness, commitment, and attraction achieved in a relationship.

Generally speaking, as CMC competence increases, coorientation, appropriateness, effectiveness, satisfaction, and preferred relational outcomes are more likely to occur. However, it is important to point out that CMC interaction is often highly strategic, and interactants sometimes elect to communicate in strategically ambiguous ways (Bavelas, Black, Chovil, & Mullett, 1990; Eisenberg, 1984; Spitzberg, 1993), and in ways that favor efficiency over appropriateness (Bertacco & Deponte, 2005; Kellermann & Shea, 1996). People often construct or perceive that they strategically select messages according to the medium of exchange (e.g., Bargh et al., 2002; Kayany et al., 1996; Markus, 1994; O'Sullivan, 2000; Rice, 1993; Rice & Shook, 1990; Sitkin et al., 1992). To the extent effectiveness is valued over appropriateness, self-satisfaction is more likely to increase relative to the satisfaction of other(s) involved in the interaction. Conversely, to the extent that appropriateness is valued over effectiveness, especially in competitive contexts, the more that self-satisfaction is likely to diminish relative to the satisfaction of others (Spitzberg, 1993, 1994a). That is, the more exploitative one's orientation, the more it comes at the expense of others involved. As an example, although deception via CMC does not appear to be a preferred strategy for most interactants, neither is it uncommon (e.g., Cornwell & Lundgren, 2001; Knox et al., 2001; Pew, 2001; Rumbough, 2001; Whitty, 2002).

CMC users vary their media selection based on their impressions of appropriateness and effectiveness (Rice, 1993; Tidwell & Walther, 2002), and these proximal criteria are likely to be supportive of more terminal goals and objectives. Thus, a reasonably generalizable working typology of outcomes of CMC competence is appropriateness, effectiveness (including task achievement and efficiency), coorientation, satisfaction, and relationship development. Generally, these outcomes should be positively related to CMC competence, yet, in any given context, communicators may strategically sacrifice one or more outcomes for others, especially when the outcomes are perceived to be mutually incompatible.

1. Competence outcomes (i.e., appropriateness, effectiveness, coorientation, satisfaction, and relational development) are positively related to one another but not isomorphic.
2. CMC motivation is positively related to competence outcomes (i.e., appropriateness, effectiveness, coorientation, satisfaction, and relational development).
3. CMC knowledge is positively related to competence outcomes (i.e., appropriateness, effectiveness, coorientation, satisfaction, and relational development).
4. CMC skills (i.e., attentiveness, composure, coordination, and expressiveness) are positively related to competence outcomes (i.e., appropriateness, effectiveness, coorientation, satisfaction, and relational development).

A Theory of CMC Competence

The basic elements of the theoretical model of CMC competence are visually represented in Figure 1. This model proposes that motivation represents the initial energizing process of knowledge search and application, which manifest through the selection of skills that are applied to the selection of media and messages. Certain motivations are better served by certain media features (e.g., a shy person may prefer an online dating system that permits more lurking than participating) and messages (e.g., a high status person may prefer efficiency and task-orientation of message content). Knowledge of the most competent messages and media is searched and selected accordingly and subsequently implemented through the skills of CMC. The messages transmitted through the selected media are filtered through the receivers' expectations for messages in those media. Those expectancies are products of the receivers' experiences with CMC and of the receivers' culture, sense of chronemics, relationship, environment, and the anticipated function of the messages. Through ongoing interaction, these expectancies are fulfilled, violated, or renegotiated, and the product of the message exchange and the degree to which expectancies are fulfilled or violated predicts the outcomes of the process for both the original sender and the co-interactant(s).

Obviously, many of the previous propositions are predicated on prior conceptualizations of interpersonal competence (see Spitzberg, 1994c, 2000; Spitzberg & Brunner, 1991; Spitzberg & Cupach, 1984, 2002), although other models have demonstrated the relevance of similar constructs (e.g., Levine & Donitsa-Schmidt, 1998). To this point, the components of the CMC competence model have been conceptualized largely from an individual differences perspective, but in keeping with the reasoning of summative, compensatory, and interactive effects (Spitzberg & Cupach, 1984), it is assumed that, in general, competent interactants can facilitate the competence of co-interactants. While the reverse may be true (i.e., an incompetent interactant can diminish a normally competent co-interactant's performance), part of the benefit of competence is the ability to compensate for the incompetence of other(s).

One of the component relationships only alluded to thus far is the issue of congruence. Specifically, Spitzberg and Brunner (1991) predict a valence reversal of competence impressions. When positive expectancies are fulfilled, outcomes are generally positive. When negative expectancies are fulfilled, outcomes are generally negative. These commonsense predictions anticipate main effects for congruence. In contrast, if interactants expect negative outcomes, the most competent response is to violate those expectancies appropriately. Conversely, violation of positive expectancies is likely to produce unpleasant or dispreferred outcomes. These predictions anticipate interaction effects between the valence of expectancy and the valence of response. Contrary to the interaction effects, a recent experiment found that positively valenced email responses were viewed as more competent regardless of the valence of expectancy (Ladwig & Spitzberg, 2005). If replicated, such findings will call for the modification of the expectancies components of the theory, although there is sufficient evidence for the role of expectancies in FtF interaction to retain their theoretical role until further research can be conducted. The other propositions follow from the original model of communication competence or from integration of prior CMC research with the model.

1. Congruence of CMC messages with prior positively valenced (contextual, message, and media) expectancies is positively related to competence outcomes.
2. Incongruence of CMC messages with prior negatively valenced (contextual, message, and media) expectancies is positively related to competence outcomes.
3. Congruence of CMC messages with prior negatively valenced (contextual, message, and media) expectancies is negatively related to competence outcomes.
4. Incongruence of CMC messages with prior positively valenced (contextual, message, and media) expectancies is negatively related to competence outcomes.
5. As interactant's (i.e., sender's) CMC competence increases, co-interactant's (i.e., receiver's) CMC competence increases.
6. As interactant (i.e., sender) pursues outcomes that preference personal effectiveness, coorientation, or satisfaction over appropriateness, the lower co-interactant's (i.e., receiver) perceptions of sender's CMC competence, and the lower receiver's outcomes.
7. As mutual CMC motivation, knowledge, and skills increase, mutual relationship development increases.

Preliminary Measure and Test

Measurement development efforts in the CMC context are evolving rapidly (e.g., Ambra & Rice, 2001; Caplan, 2002; Gaudron & Vignoli, 2002; Richter et al., 2000). Research on the CMC competence model is nascent. An a priori measure was developed on the basis of the model in Figure 1 and subsequently revised on several occasions. The original measure was used in a study by Harper (1999). Unfortunately, the data were not analyzed in a manner conducive to drawing conclusions regarding the measure's reliability or validity. Research was subsequently collected and analyzed in projects by Bubaš (2002, 2005), Bunz (2002, 2003), and Van Slooten and Spitzberg (2002). Although the preliminary measure generally revealed promise, at least two important problems re-occurred across these studies. First, the negatively worded items in the subscales of the measure tended to attenuate the reliability of the scales, especially those scales with few items. Second, the various items designed to measure context, message, and media factors were not as multidimensionally complex as originally anticipated. As a result of these findings, the measure was significantly simplified with the objective of increasing the reliability and parsimony of the overall measure. Measures of related constructs are already available (e.g., Burgoon et al., 2002; Parks & Roberts, 1998). The current measure is at present being prepared for data collection. Preliminary results from a study of an online version in Croatia indicate that when all items are factor-analyzed, four reliable factors emerge that roughly parallel motivation, knowledge, skills, and outcomes (Bubaš et al., 2003).

Conclusion

The potential applications of a model and measure of CMC competence are manifold. For example, it seems reasonable to expect that as CMC competence increases, loneliness, depression, and computer-based stresses and hassles will decrease. Given that CMC competence is correlated with use and experience, it may in fact be positively related to overall risk of cyberstalking victimization (Finkelhor, Mitchell, & Wolak, 2000; Spitzberg & Hoobler, 2002; cf. Wolak et al., 2002), but holding such opportunity costs constant, it seems reasonable to expect that more competent CMC users would be less likely to be victimized than less competent users. As a screening device, a model and measure of CMC competence may be useful in diagnosing those in greater need of earlier intervention in schools and organizations. As the digital divide dilates or dissolves, it becomes increasingly important to understand the factors that enhance users' abilities to navigate and negotiate the divide's turbulent currents.

In proposing this theory of CMC competence, I have suggested its nature, function, and scope, as well as its research implications. The theory does not have a primary motivational metaphor, such as the naive scientist (attribution theory), investor (social exchange theory), information processor (uncertainty reduction theory), comparator (sociometer theory), and so on. Instead, motivation, knowledge, skills, context, and outcomes serve as metaphorical vessels into which prior and future research can be functionally ensconced. At some level, it is presumed that there are real, reducible parallels that serve as the substance of motivation, the substance of knowledge, and the substance of skills, which are moderated by real contextual factors in their influence on real outcomes. Collectively, the CMC theory is ontologically consistent with both traditional causal and teleological systems perspectives.

Another presumption of the model is that FtF and CMC interaction are more similar than they are different. Both can be explained by the same general model components, and, in most cases, the components of this model require only minor adaptation to the particular technological features of the context. As such, the parameters of the model are that it is proposed presently for all mediated interpersonal types of communication (thereby excluding traditional mass communication types of contexts in which relatively singular messages are distributed to large, relatively undifferentiated groups of individuals). The primary value of the model is in outlining a heuristic schema for reorganizing much disparate literature into a semantic model that can generate coherent hypotheses.

References

Althaus, S. L. (1997). Computer-mediated communication in the university classroom: An experiment with on-line discussions. Communication Education, 46 (3), 158-174.

Ambra, J. D., & Rice, R. E. (2001). Emerging factors in user evaluation of the World Wide Web. Information & Management, 38 (6), 373-384.

Amichai-Hamburger, Y., & Ben-Artzi, E. (2003). Loneliness and Internet use. Computers in Human Behavior, 19 (1), 71-80.

Argyle, M., Furnham, A., & Graham, J. A. (1981). Social Situations. Cambridge: Cambridge University Press.

Ashmore, M. (1989). The Reflexive Thesis: Wrighting Sociology of Scientific Knowledge. Chicago: University of Chicago Press.

Barbeite, F. G., & Weiss, E. M. (2004). Computer self-efficacy and anxiety scales for an Internet sample: Testing measurement equivalence of existing measures and development of new scales. Computers in Human Behavior, 20 (1), 1-15.

Bargh, J. A. (2002). Beyond simple truths: The human-internet interaction. Journal of Social Issues, 58 (1), 1-8.

Bargh, J. A., McKenna, K. Y. A., & Fitzsimons, G. M. (2002). Can you see the real me? Activation and expression of the "true self" on the Internet. Journal of Social Issues, 58 (1), 33-78.

Bavelas, J. B., Black, A., Chovil, N. & Mullett, J. (1990). Equivocal Communication. Newbury Park, CA: Sage.

Baym, N. K., Zhang, Y. B., & Lin, M.-C. (2004). Social interactions across media. New Media & Society, 6 (3), 299-318.

Beckers, J. J., & Schmidt, H. G. (2001). The structure of computer anxiety: A six-factor model. Computers in Human Behavior, 17 (1), 35-49.

Bertacco, M., & Deponte, A. (2005). Email as a speed-facilitating device: A contribution to the reduced-cues perspective on communication. Journal of Computer-Mediated Communication, 10 (3), article 2. Retrieved January 21, 2006 from http://jcmc.indiana.edu/vol10/issue3/bertacco.html

Bozionelos, N. (2002). Computer interest: A case for expressive traits. Personality and Individual Differences, 33 (3), 427-444.

Brandon, D. P., & Hollingshead, A. B. (1999). Collaborative learning and computer-supported groups. Communication Education, 48 (2), 109-126.

Brenner, V. (1997). Psychology of computer use: XLVII. Parameters of Internet use, abuse, and addiction: The first 90 days of the Internet usage survey. Psychological Reports, 80 (3), 879-882.

Brosnan, M., & Lee, W. (1998). A cross-cultural comparison of gender differences in computer attitudes and anxieties: The United Kingdom and Hong Kong. Computers in Human Behavior, 14 (4), 550-577.

Bubaš, G. (2002). Unpublished data. University of Zagreb, Croatia.

Bubaš, G. (2005). Competence in Computer-Mediated Communication: An Evaluation and Potential Uses of a Self-Assessment Measure. Manuscript submitted for presentation consideration, University of Zagreb, Croatia.

Bubaš, G., & Aurer, B. (1998). Non-technical competencies required for information technology professionals: How to effectively interact with clients/users. Zbornik radova: Journal of Information and Organizational Sciences, 22 (1), 41-52.

Bubaš, G., & Hutinski, Z. (2003, May). Conceptual model, empirically derived predictors and potential dimensions of Internet affinity. Manuscript submitted for presentation consideration, University of Zagreb, Croatia.

Bubaš, G., Radošević, D., & Hutinski, Ž. (2003, September). Assessment of computer mediated communication competence: Theory and application in an online environment. Paper presented at the 14th International Conference on Information and Intelligent Systems, Varaždin, Croatia.

Bunz, U. (2002, May). Shifting frontiers: Passing from computer literacy into computer-mediated communication competency territory. Paper presented at the 53rd International Communication Association Conference, San Diego, CA.

Bunz, U. (2003). Growing from computer literacy towards computer-mediated communication competence: Evolution of a field and evaluation of a new measurement instrument. Information Technology, Education and Society, 4 (2), 53-84.

Bunz, U. (2004). The computer-email-web (CEW) fluency scale—Development and validation. International Journal of Human-Computer Interaction, 17 (4), 479-506.

Bunz, U., & Campbell, S. W. (2004). Politeness accommodation in electronic mail. Communication Research Reports, 21 (1), 11-25.

Burgoon, J. K., Bonito, J. A., Bengtsson, B., Cederberg, C., Lundeberg, M., & Allspach, L. (2000). Interactivity in human-computer interaction: A study of credibility, understanding, and influence. Computers in Human Behavior, 16 (6), 553-574.

Burgoon, J. K., Bonito, J. A., Ramirez, A., Jr., Dunbar, N. E., Kam, K., & Fischer, J. (2002). Testing the interactivity principle: Effects of mediation, propinquity, and verbal and nonverbal modalities of interpersonal interaction. Journal of Communication, 52 (3), 657-677.

Cai, X. (2004). Is the computer a functional alternative to traditional media? Communication Research Reports, 21 (1), 26-38.

Campbell, S. W., & Neer, M. R. (2001). The relationship of communication apprehension and interaction involvement to perceptions of computer-mediated communication. Communication Research Reports, 18 (4), 391-398.

Caplan, S. E. (2002). Problematic Internet use and psychosocial well-being: Development of a theory-based cognitive-behavioral measurement instrument. Computers in Human Behavior, 18 (5), 553-575.

Castellá, V. O., Abad, A. M. Z., Alonso, F. P., & Silla, J. M. P. (2000). The influence of familiarity among group members, group atmosphere, and assertiveness on uninhibited behavior through three different communication media. Computers in Human Behavior, 16 (2), 141-159.

Cerulo, K. A. (1997). Reframing sociological concepts for a brave new (virtual?) world. Sociological Inquiry, 67 (1), 48-58.

Cheseboro, J. W. (2000). Communication technologies as symbolic form: Cognitive transformations generated by the Internet. Qualitative Research Reports in Communication, 1 (1), 8-13.

Chua, S. L., Chen, D.-T., & Wong, A. F. L. (1999). Computer anxiety and its correlates: A meta-analysis. Computers in Human Behavior, 15 (5), 609-623.

Cochrane, P. (1995). The information wave. In S. J. Emmott (Ed.), Information Superhighways: Multimedia Users and Futures (pp. 17-33). San Diego, CA: Academic.

Cooper, A. (2000). Cybersex and sexual compulsivity: The dark side of the force. In Cooper, A. (Ed.), Cybersex: The Dark Side of the Force (pp. 1-3). Philadelphia, PA: Brunner-Routledge.

Cooper, A., Delmonico, D. L., & Burg, R. (2000). Cybersex users, abusers, and compulsives: New findings and implications. Sexual Addiction & Compulsivity, 7 (1/2), 5-29.

Cornwell, B., & Lundgren, D. C. (2001). Love on the Internet: Involvement and misrepresentation in romantic relationships in cyberspace vs. realspace. Computers in Human Behavior, 17 (2), 197-211.

Corston, R., & Colman, A. M. (1996). Gender and social facilitation effects on computer competence and attitudes toward computers. Journal of Educational Computing Research, 14 (2), 171-183.

Cummings, J. N., Butler, B., & Kraut, R. (2002). The quality of online relationships. Communications of the ACM, 45 (7), 103-108.

Davis, R. A. (2001). A cognitive-behavioral model of pathological Internet use. Computers in Human Behavior, 17 (2), 187-195.

Dietz-Uhler, B., & Bishop-Clark, C. (2001). The use of computer-mediated communication to enhance subsequent face-to-face discussions. Computers in Human Behavior, 17 (3), 269-283.

Eastin, M. S., & LaRose, R. (2000). Internet self-efficacy and the psychology of the digital divide. Journal of Computer-Mediated Communication, 6 (1). Retrieved November 27, 2005 from http://jcmc.indiana.edu/vol6/issue1/eastin.html

Eisenberg, E. M. (1984). Ambiguity as strategy in organizational communication. Communication Monographs, 51 (3), 227-242.

Fang, K. (1998). An analysis of electronic mail usage. Computers in Human Behavior, 14 (2), 349-374.

Finkelhor, D., Mitchell, K. J., & Wolak, J. (2000). Online Victimization: A Report on the Nation's Youth. Alexandria, VA: National Center for Missing and Exploited Children.

Fulk, J., Schmitz, J., & Steinfield, C. W. (1990). A social influence model of technology use. In J. Fulk & C. Steinfield (Eds.), Organizations and Communication Technology (pp. 117-140). Newbury Park, CA: Sage.

Garton, L., & Wellman, B. (1995). Social impacts of electronic mail in organizations: A review of the research literature. In B. R. Burleson (Ed.), Communication Yearbook 18 (pp. 434-453). Thousand Oaks, CA: Sage.

Gaudron, J.-P., & Vignoli, E. (2002). Assessing computer anxiety with the interaction model of anxiety: Development and validation of the computer anxiety trait subscale. Computers in Human Behavior, 18 (3), 315-325.

Gergen, K. J. (1991). The Saturated Self: Dilemmas of Identity in Contemporary Life. New York: Basic Books.

Goodson, P., McCormick, D., & Evans, A. (2001). Searching for sexually explicit materials on the Internet: An exploratory study of college students' behavior and attitudes. Archives of Sexual Behavior, 30 (2), 101-118.

Greene, J. O. (1997). A second generation action assembly theory. In J. O. Greene (Ed.), Message Production: Advances in Communication Theory (pp. 151-170). Mahwah, NJ: Lawrence Erlbaum Associates.

Griffiths, M. (1999). Internet addiction: Fact or fiction? Psychologist, 12 (5), 246-250.

Griffiths, M. (2001). Sex on the Internet: Observations and implications for Internet sex addiction. Journal of Sex Research, 38 (4), 333-342.

Gross, E. F., Juvonen, J., & Gable, S. L. (2002). Internet use and well-being in adolescence. Journal of Social Issues, 58 (1), 75-90.

Hacker, K. L., & Steiner, R. (2001). Hurdles of access and benefits of usage for Internet communication. Communication Research Reports, 18 (4), 399-407.

Hancock, J. T., & Dunham, P. J. (2001). Impression formation in computer-mediated communication revisited: An analysis of the breadth and intensity of impressions. Communication Research, 28 (3), 325-347.

Hardy, B. W., & Scheufele, D. A. (2005). Examining differential gains from Internet use: Comparing the moderating role of talk and online interactions. Journal of Communication, 55 (1), 71-84.

Harper, V. B., Jr. (1999). African-American College Students' Perceptions of Computer-Mediated Communication (CMC) Competence: An Exploratory Study. Washington, DC: Howard University.

Harper, V. B., Jr. (2002). Sex differences in perceived outcomes of electronic mail interactions. Psychological Reports, 90 (2), 701-702.

Harrison, A. W., & Rainer, R. K., Jr. (1996). A general measure of user computing satisfaction. Computers in Human Behavior, 12 (1), 79-92.

Hart, W. B. (1998). Intercultural computer-mediated communication (ICCMC). The Edge: The E-Journal of Intercultural Relations, 1 (4). Retrieved January 21, 2006 from http://interculturalrelations.com/v1i4Fall1998/f98hart.htm

Havighurst, R. J. (1957). The social competence of middle-aged people. Genetic Psychology Monographs, 56 (2), 297-375.

Hawes, L. C. (1975). Pragmatics of Analoguing: Theory and Model Construction in Communication. Reading, MA: Addison-Wesley.

Heise, D. R. (1979). Understanding Events: Affect and the Construction of Social Action. Cambridge: Cambridge University Press.

Herring, S. C. (2001). Gender and power in online communication. CSI Working Paper (No. WP-01-05). Retrieved January 21, 2006 from http://rkcsi.indiana.edu/archive/CSI/WP/WP01-05B.html

Herring, S. C. (2004). Slouching toward the ordinary: Current trends in computer-mediated communication. New Media & Society, 6 (1), 26-36.

Herring, S. C., & Martinson, A. (2004). Assessing gender authenticity in computer-mediated language use: Evidence from an identity game. Journal of Language and Social Psychology, 23 (4), 424-446.

Hiltz, S. R. (1986). The "virtual classroom:" Using computer-mediated communication for university teaching. Journal of Communication, 36 (2), 95-104.

Hollingshead, A. B., McGrath, J. E., & O'Connor, K. M. (1993). Group task performance and communication technology: A longitudinal study of computer-mediated versus face-to-face work groups. Small Group Research, 24 (3), 307-333.

Hovick, S. R. A., Meyers, R. A., & Timmerman, C. E. (2003). E-mail communication in workplace romantic relationships. Communication Studies, 54 (4), 468-482.

Hunter, J., & Allen, M. (1992). Adaptation to electronic mail. Journal of Applied Communication Research, 20 (3), 254-274.

Hutchby, I. (2001). Conversation and Technology: From the Telephone to the Internet. Cambridge: Polity.

Inose, H., & Pierce, J. R. (1984). Information Technology and Civilization. New York: W. H. Freeman.

Internet World Stats. (2005). Internet Usage Statistics—The Big Picture. Retrieved July 25, 2005 from http://www.internetworldstats.com/stats.htm

Jones, S. (2002). The Internet Goes to College: How Students are Living in the Future with Today's Technology. Washington, DC: Pew Internet & American Life Project.

Kedzie, C. R. (1997). A brave new world or a new world order? In S. Kiesler (Ed.), Culture of the Internet (pp. 209-232). Mahwah, NJ: Lawrence Erlbaum Associates.

Kayany, J. M., Wotring, C. E., & Forrest, E. J. (1996). Relational control and interactive media choice in technology-mediated communication situations. Human Communication Research, 22 (3), 399-421.

Kellermann, K., & Shea, B. C. (1996). Threats, suggestions, hints, and promises: Gaining compliance efficiently and politely. Communication Quarterly, 44 (2), 145-165.

Knox, D., Daniels, V., Sturdivant, L., & Zusman, M. E. (2001). College student use of the Internet for mate selection. College Student Journal, 35 (1), 158-160.

Koutougos, A. (1989). Research programmes and paradigms as dialogue structures. In K. Gavroglu, Y. Goudaroulis, & P. Nicolacopoulos (Eds.), Boston Studies in the Philosophy of Science: Vol. 111. Imre Lakatos and Theories of Scientific Change (pp. 361-374). Boston: Kluwer Academic.

Kraut, R., Kiesler, S., Boneva, B., Cummings, J., Helgeson, V., & Crawford, A. (2002). Internet paradox revisited. Journal of Social Issues, 58 (1), 49-74.

Kraut, R., Patterson, M., Lundmark, V., Kiesler, S., Mukopadhyay, T., & Scherlis, W. (1998). Internet paradox: A social technology that reduces social involvement and psychological well-being? American Psychologist, 53 (9), 1017-1031.

Ladwig, M. A., & Spitzberg, B. H. (2005). Great Expectations: An Expectancy Approach to Computer-Mediated Communication Competence. Manuscript submitted for conference presentation.

Lakatos, I. (1970). Falsification and the methodology of scientific research programmes. In I. Lakatos & A. Musgrave (Eds.), Proceedings of the International Colloquium in the Philosophy of Science: Vol. 4. Criticism and the Growth of Knowledge (pp. 91-196). Cambridge: Cambridge University.

LaLomia, M. J., & Sidowski, J. B. (1990). Measurements of computer satisfaction: Literacy, and aptitudes: A review. International Journal of Human-Computer Interaction, 2 (3), 231-253.

LaRose, R., Eastin, M. S., & Gregg, J. (2001). Reformulating the Internet paradox: Social cognitive explanations of Internet use and depression. Journal of Online Behavior, 1 (2). Retrieved October 14, 2002 from http://www.behavior.net/job/v1n2/paradox.html

Lea, M., & Spears, R. (1995). Love at first byte? Building personal relationships over computer networks. In J. T. Wood & S. Duck (Eds.), Under-Studied Relationships: Off the Beaten Track (pp. 197-233). Thousand Oaks, CA: Sage.

Lenhart, A., Madden, M., & Hitlin, P. (2005). Teens and Technology: Youth are Leading the Transition to a Fully Wired and Mobile Nation. Washington DC: Pew Internet & American Life Project.

Levine, T., & Donitsa-Schmidt, S. (1998). Computer use, confidence, attitudes, and knowledge: A causal analysis. Computers in Human Behavior, 14 (1), 125-146.

Markey, P. M., & Wells, S. M. (2002). Interpersonal perception in Internet chat rooms. Journal of Research in Personality, 36 (2), 134-146.

Markus, M. L. (1994). Finding a happy medium: Explaining the negative effects of electronic communication on social life at work. ACM Transactions on Information Systems, 12 (2), 119-149.

Mazur, M. A., Burns, R. J., & Emmers-Sommer, T. M. (2000). Perceptions of relational interdependence in online relationships: The effects of communication apprehension and introversion. Communication Research Reports, 17 (4), 397-406.

McCown, J. A., Fischer, D., Page, R., & Homant, M. (2001). Internet relationships: People who meet people. CyberPsychology & Behavior, 4 (5), 593-596

McGrath, M. G., & Casey, E. (2002). Forensic psychiatry and the Internet: Practical perspectives on sexual harassers in cyberspace. Journal of the American Academy of Psychiatry and the Law, 30 (1), 81-94.

McKenna, K. Y. A., Green, A. S., & Gleason, M. E. J. (2002). Relationship formation on the Internet: What's the big attraction? Journal of Social Issues, 58 (1), 9-32.

McQuail, D., & Windahl, S. (1993). Communication Models for the Study of Mass Communication (2nd ed.). New York: Longman.

McQuillen, J. S. (2003). The influence of technology on the initiation of interpersonal relationships. Education, 123 (3), 616-623.

Meyrowitz, J. (1985). No Sense of Place: The Impact of Electronic Media on Social Behavior. New York: Oxford University Press.

Morahan-Martin, J., & Schumacher, P. (2000). Incidence and correlates of pathological Internet use among college students. Computers in Human Behavior, 16 (1), 13-29.

Morahan-Martin, J., & Schumacher, P. (2003). Loneliness and social uses of the Internet. Computers in Human Behavior, 19 (6), 659-671.

Morreale, S. P., Spitzberg, B. H., & Barge, J. K. (2001). Human Communication: Motivation, Knowledge, & Skills. Belmont, CA: Wadsworth.

Nice, M. L., & Katzev, R. (1998). Internet romances: The frequency and nature of romantic on-line relationships. CyberPsychology & Behavior, 1 (3), 217-223.

Nie, N. H., & Erbring, L. (2000). Internet and Society: A Preliminary Report. Retrieved June 13, 2001 from the Stanford Institute for the Quantitative Study of Society Web site http://www.Stanford.edu/group/siqss/press_release/preliminary_report.pdf

O'Sullivan, P. B. (2000). What you don't know won't hurt me: Impression management functions of communication channels in relationships. Human Communication Research, 26 (3), 403-431.

O'Sullivan, P. B., & Flanagin, A. J. (2003). Reconceptualizing 'flaming' and other problematic messages. New Media & Society, 5 (1), 69-94.

Papineau, D. (1989). Has Popper been a good thing? In K. Gavroglu, Y. Goudaroulis, & P. Nicolacopoulos (Eds.), Boston Studies in the Philosophy of Science: Vol. 111. Imre Lakatos and Theories of Scientific Change (pp. 431-440). Boston: Kluwer Academic.

Parks, M. R., & Floyd, K. (1996). Making friends in cyberspace. Journal of Communication, 46 (1), 80-97.

Parks, M. R., & Roberts, L. D. (1998). 'Making MOOsic:' The development of personal relationships on line and a comparison to their off-line counterparts. Journal of Social and Personal Relationships, 15 (4), 517-537.

Patterson, B. R., & Gojdycz, T. K. (2000). The relationship between computer-mediated communication and communication related anxieties. Communication Research Reports, 17 (3), 278-287.

Peris, R., Gimeno, M. A., Pinazo, D., Ortet, G., Carrero, V., Sanchiz, M., & Ibañez, I. (2002). Online chat rooms: Virtual spaces of interaction for socially oriented people. CyberPsychology & Behavior, 5 (1), 43-51.

Perse, E. M., & Ferguson, D. A. (2000). The benefits and costs of web surfing. Communication Quarterly, 48 (4), 343-359.

Pew Internet & American Life Project. (2000, May 10). Tracking Online Life: How Women Use the Internet to Cultivate Relationships With Family and Friends. Washington DC: Author.

Pew Internet & American Life Project. (2001, June 20). Teenage Life Online: The Rise of the Instant-Message Generation and the Internet's Impact on Friendships and Family Relationships. Washington DC: Author.

Potosky, D., & Bobko, P. (1998). The computer understanding and experience scale: A self-report measure of computer experience. Computers in Human Behavior, 14 (2), 337-348.

Pratarelli, M. C., Browne, B. L., & Johnson, K. (1999). The bits and bytes of computer/Internet addiction: A factor analytic approach. Behavior Research Methods, Instruments, & Computers, 31 (2), 305-314.

Pratt, L., Wiseman, R. L., Cody, M. J., & Wendt, P. F. (1999). Interrogative strategies and information exchange in computer-mediated communication. Communication Quarterly, 47 (1), 46-66.

Preece, J., Nonnecke, B., & Andrews, D. (2004). The top five reasons for lurking: Improving community experiences for everyone. Computers in Human Behavior, 20 (2), 201-223.

Ramirez, A., Jr., Walther, J. B., Burgoon, J. K., & Sunnafrank, M. (2002). Information-seeking strategies, uncertainty, and computer-mediated communication: Toward a conceptual model. Human Communication Research, 28 (2), 213-228.

Rice, R. E. (1993). Media appropriateness: Using social presence theory to compare traditional and new organizational media. Human Communication Research, 19 (4), 451-484.

Rice, R. E., D'Ambra, J., & More, E. (1998). Cross-cultural comparison of organizational media evaluation and choice. Journal of Communication, 48 (3), 3-26.

Rice, R. E., & Shook, D. E. (1990). Relationships of job categories and organizational levels to use of communication channels, including electronic mail: A meta-analysis and extension. Journal of Management Studies, 27 (2), 195-229.

Richter, T., Naumann, J., & Groeben, N. (2000). Attitudes toward the computer: Construct validation of an instrument with scales differentiated by content. Computers in Human Behavior, 16 (5), 473-491.

Rideout, V., Roberts, D. F., & Foehr, U. G. (2005). Generation M: Media in the Lives of 8-18 Year-Olds. Washington DC: Kaiser Family Foundation.

Ring, K., & Wallston, K. (1968). A test to measure performance styles in interpersonal relations. Psychological Reports, 22 (1), 147 154.

Ring, K., Braginsky, D., & Braginsky, B. (1966). Performance styles in interpersonal relations: A typology. Psychological Reports, 18 (1), 203 220.

Ring, K., Braginsky, D., Levine, L., & Braginsky, B. (1967). Performance styles in interpersonal behavior: An experimental validation of a topology. Journal of Experimental Social Psychology, 3 (2), 140 159.

Rosen, L. D., & Weil, M. M. (1995). Computer anxiety: A cross-cultural comparison of university students in ten countries. Computers in Human Behavior, 11 (1), 45-64.

Rouse, S. V., & Haas, H. A. (2003). Exploring the accuracies and inaccuracies of personality perception following Internet-mediated communication. Journal of Research in Personality, 37 (5), 446-467.

Rubin, R. B. (1983). Conclusions. In R. B. Rubin (Ed.), Improving Speaking and Listening Skills (pp. 95-100). San Francisco: Jossey Bass.

Rumbough, T. (2001). The development and maintenance of interpersonal relationships through computer-mediated communication. Communication Research Reports, 18 (3), 223-229.

Savicki, V., Kelley, M., & Oesterrich, E. (1999). Judgments of gender in computer-mediated communication. Computers in Human Behavior, 15 (2), 185-194.

Scharlott, B. W., & Christ, W. G. (1995). Overcoming relationship-initiation barriers: The impact of a computer-dating system on sex role, shyness, and appearance inhibitions. Computers in Human Behavior, 11 (2), 191-204.

Schneider, J. P. (2000). Effects of cybersex addiction on the family: Results of a survey. Sexual Addiction & Compulsivity, 7 (1/2), 31-58.

Schwartz, M. F., & Southern, S. (2000). Compulsive cybersex: The new tea room. Sexual Addiction & Compulsivity, 7 (1/2), 124-144.

Séguin-Levesque, C., Laliberté, M. L. N., Pelletier, L. G., Blanchard, C., & Vallerand, R. J. (2003). Harmonious and obsessive passion for the Internet: Their associations with the couple's relationship. Journal of Applied Social Psychology, 33 (1), 197-221.

Sheehan, K. B., & Hoy, M. G. (1999). Flaming, complaining, abstaining: How online users respond to privacy concerns. Journal of Advertising, 28 (3), 37-51.

Sheehy, N. (1995). Designing organizations using telematic technologies: Risks and benefits. In S. J. Emmott (Ed.), Information Superhighways: Multimedia Users and Futures (pp. 103-119). San Diego, CA: Academic.

Shields, P., & Samarajiva, R. (1993). Competing frameworks for research on information-communication technologies and society: Toward a synthesis. In S. A. Deetz (Ed.), Communication Yearbook 16 (pp. 349-380). Newbury Parks, CA: Sage.

Sitkin, S. B., Sutcliffe, K. M., & Barrios-Choplin, J. R. (1992). A dual-capacity model of communication media choice in organizations. Human Communication Research, 18 (4), 563-598.

Smith, B., Caputi, P., Crittenden, N., Jayasuriya, R., & Rawstorne, P. (1999). A review of the construct of computer experience. Computers in Human Behavior, 15 (2), 227-242.

Smith, B., Caputi, P., & Rawstone, P. (2000). Differentiating computer experience and attitudes toward computers: An empirical investigation. Computers in Human Behavior, 16 (1), 59-81.

Sohn, D., & Lee, B.-K. (2005). Dimensions of interactivity: Differential effects of social and psychological factors. Journal of Computer-Mediated Communication, 10 (3), article 6. Retrieved November 27, 2005 from http://jcmc.indiana.edu/vol10/issue3/sohn.html

Spears, R., Postmes, T., Lea, M., & Wolbert, A. (2002). When are net effects gross products? The power of influence and the influence of power in computer-mediated communication. Journal of Social Issues, 58 (1), 91-108.

Spitzberg, B. H. (1983). Communication competence as knowledge, skill, and impression. Communication Education, 32 (3), 323 328.

Spitzberg, B. H. (1990). The construct validity of trait-based measures of interpersonal competence. Communication Research Reports, 7 (2), 107-116.

Spitzberg, B. H. (1991). An examination of trait measures of interpersonal competence. Communication Reports, 4, 22-29.

Spitzberg, B. H. (1993). The dialectics of (in)competence. Journal of Social and Personal Relationships, 10 (1), 137-158.

Spitzberg, B. H. (1994a). The dark side of (in)competence. In W. R. Cupach & B. H. Spitzberg (Eds.), The Dark Side of Interpersonal Communication (pp. 24-50). Hillsdale, NJ: Lawrence Erlbaum Associates.

Spitzberg, B. H. (1994b). Instructional assessment of interpersonal competence: The Conversational Skills Rating Scale. In S. Morreale, M. Brooks, R. Berko, & C. Cooke (Eds.), 1994 SCA Summer Conference Proceedings: Assessing College Student Competency in Speech Communication (pp. 325-352). Annandale, VA: Speech Communication Association.

Spitzberg, B. H. (1994c). Intercultural effectiveness. In L.A. Samovar & R.E. Porter (Eds.), Intercultural Communication: A Reader (7th ed., pp. 347-359). Belmont, CA: Wadsworth.

Spitzberg, B. H. (2000). What is good communication? Journal of the Association for Communication Administration, 29, 103-119.

Spitzberg, B. H., Brookshire, R. G., & Brunner, C. C. (1990). The factorial domain of interpersonal skills. Social Behavior and Personality, 18 (1), 137-150.

Spitzberg, B. H., & Brunner, C. C. (1991). Toward a theoretical integration of context and communication competence inference research. Western Journal of Speech Communication, 55 (1), 28-46.

Spitzberg, B. H., & Cupach, W. R. (1984). Interpersonal Communication Competence. Beverly Hills, CA: Sage.

Spitzberg, B. H., & Cupach, W. R. (2002). Interpersonal skills. In M. L. Knapp & J. A. Daly (Eds.), Handbook of Interpersonal Communication (pp. 564-611). Thousand Oaks, CA: Sage.

Spitzberg, B. H., & Hecht, M. L. (1984). A component model of relational competence. Human Communication Research, 10 (4), 575 599.

Spitzberg, B. H., & Hoobler, G. (2002). Cyberstalking and the technologies of interpersonal terrorism. New Media & Society, 4 (1), 71-92.

Spitzberg, B. H., & Hurt, H. T. (1987). The measurement of interpersonal skills in instructional contexts. Communication Education, 36 (1), 28 45.

Straus, S. G., Miles, J. A., & Levesque, L. L. (2001). The effects of videoconference, telephone, and face-to-face media on interviewer and applicant judgments in employment interviews. Journal of Management, 27 (3), 363-381.

Suler, J. R. (1999). To get what you need: Healthy and pathological Internet use. CyberPsychology & Behavior, 2 (5), 385-393.

Sussman, N. M., & Tyson, D. H. (2000). Sex and power: Gender differences in computer-mediated interactions. Computers in Human Behavior, 16 (4), 381-394.

Tanis, M., & Postmes, T. (2003). Social cues and impression formation in CMC. Journal of Communication, 53 (4), 676-693.

Tewksbury, D., & Althaus, S. L. (2000). An examination of motivations for using the World Wide Web. Communication Research Reports, 17 (2), 127-138.

Thompson, L., & Nadler, J. (2002). Negotiating via information technology: Theory and application. Journal of Social Issues, 58 (1), 125-142.

Thompson, P. A., & Foulger, D. A. (1996). Effects of pictographs and quoting on flaming in electronic mail. Computers in Human Behavior, 12 (2), 225-243.

Tidwell, L. C., & Walther, J. B. (2002). Computer-mediated communication effects on disclosure, impressions, and interpersonal evaluations: Getting to know one another a bit at a time. Human Communication Research, 28 (3), 317-348.

Turkle, S. (1995). Life on the Screen: Identity in the Age of the Internet. New York: Simon & Schuster.

Turner, J. H. (1985). In defense of positivism. Sociological Theory, 3 (2), 24-30.

Turner, J. H. (1990). The misuse and use of metatheory. Sociological Forum, 5 (1), 37-53.

U. S. Department of Commerce. (1998). The Emerging Digital Economy. Washington DC: U. S. Department of Commerce.

Utz, S. (2000). Social information processing in MUDs: The development of friendships in virtual worlds. Journal of Online Behavior, 1 (1). Retrieved October 14, 2002 from http://www.behavior.net/job/v1n1/utz.html

van den Hooff, B., Groot, J., & de Jonge, S. (2005). Situational influences on the use of communication technologies. Journal of Business Communication, 42 (1), 4-27.

Van Slooten, P., & Spitzberg, B. H. (2002). Unpublished raw data.

Wachter, R. M. (1999). The effect of gender and communication mode on conflict resolution. Computers in Human Behavior, 15 (6), 763-782.

Walther, J. B. (1996). Computer-mediated communication: Impersonal, interpersonal, and hyperpersonal interaction. Communication Research, 23, 3-43.

Walther, J. B. (1997). Group and interpersonal effects in international computer-mediated collaboration. Human Communication Research, 23 (1), 342-369.

Walther, J. B., Anderson, J. F., & Park, D. W. (1994). Interpersonal effects in computer-mediated interaction: A meta-analysis of social and antisocial communication. Communication Research, 21 (4), 460-487.

Walther, J. B., & Parks, M. R. (2002). Cues filtered out, cues filtered in: Computer-mediated communication and relationships. In M. L. Knapp & J. A. Daly (Eds.), Handbook of Interpersonal Communication (3rd ed., pp. 529-563). Thousand Oaks, CA: Sage.

Walther, J. B., & Tidwell, L. C. (1995). Nonverbal cues in computer-mediated communication, and the effect of chronemics on relational communication. Journal of Organizational Computing & Electronic Commerce, 5 (4), 355-378.

Wästlund, E., Norlander, T., & Archer, T. (2001). Internet blues revisited: Replication and extension of an Internet paradox study. CyberPsychology & Behavior, 4 (3), 385-391.

Westmyer, S. A., DiCioccio, R. L., & Rubin, R. B. (1998). Appropriateness and effectiveness of communication channels in competent interpersonal communication. Journal of Communication, 48 (3), 27-48.

Wheeless, L. R., Eddleman-Spears, L., Magness, L. D., & Preiss, R. W. (2005). Informational reception apprehension and information from technology aversion: Development and test of a new construct. Communication Quarterly, 53 (2), 143-158.

Whitley, B. E., Jr. (1997). Gender differences in computer-related attitudes and behavior: A meta-analysis. Computers in Human Behavior, 13 (1), 1-22.

Whitty, M. T. (2002). Liar, liar! An examination of how open, supportive and honest people are in chat rooms. Computers in Human Behavior, 18 (4), 343-352.

Whitty, M. T. (2003). Cyber-flirting: Playing at love on the Internet. Theory & Psychology, 13 (3), 330-357.

Wolak, J., Mitchell, K. J., & Finkelhor, D. (2002). Close online relationships in a national sample of adolescents. Adolescence, 37 (147), 441-455.

Wolak, J., Mitchell, K. J., & Finkelhor, D. (2003). Escaping or connecting? Characteristics of youth who form close online relationships. Journal of Adolescence, 26 (1), 105-119.

Wright, K. B. (2000). Social support satisfaction, on-line communication apprehension, and perceived life stress within computer-mediated support groups. Communication Research Reports, 17 (2), 139-147.

Yuan, Y., Fulk, J., Shumate, M., Monge, P. R., Bryant, J. A., Matsaganis, M. (2005). Individual participation in organizational informational commons: The impact of team level social influence and technology-specific competence. Human Communication Research, 31 (2), 212-240.

Appendix 1: CMC Competence measure (version 5)

CMC COMPETENCE
(Spitzberg, © 2005, V.5)

Instructions: We are interested in how people use various computer-mediated communication (CMC) technologies for conversing with others. For the purpose of this questionnaire, please consider CMC to include all forms of email and computer-based networks (e.g., instant messaging, world-wide-web, chat rooms, personal data assistant, electronic bulletin boards, terminal-based video-telephony, etc.) for sending and receiving written messages with other people. For this survey, indicate the degree to which each statement regarding your use of various CMC media is true or untrue of you, using the following scale:

1 = NOT AT ALL TRUE OF ME
2 = MOSTLY NOT TRUE OF ME
3 = NEITHER TRUE NOR UNTRUE OF ME; UNDECIDED
4 = MOSTLY TRUE OF ME
5 = VERY TRUE OF ME

MOTIVATION
__01. I enjoy communicating using computer media.
__02. I am nervous about using the computer to communicate with others. [R]
__03. I am very motivated to use computers to communicate with others.
__04. I look forward to sitting down at my computer to write to others.
__05. Communicating through a computer makes me anxious [R]

KNOWLEDGE
__06. I am very knowledgeable about how to communicate through computers.
__07. I am never at a loss for something to say in CMC.
__08. I am very familiar with how to communicate through email and the internet.
__09. I always seem to know how to say things the way I mean them using CMC.
__10. When communicating with someone through a computer, I know how to adapt my messages to the medium.

EFFICACY
__11. I don't feel very competent in learning and using communication media technology.
__12. I feel completely capable of using almost all currently available CMCs.
__13. I am confident I will learn how to use any new CMCs that are due to come out.
__14. I'm nervous when I have to learn how to use a new communication technology.
__15. I find changes in technologies very frustrating.
__16. I quickly figure out how to use new CMC technologies.
__17. I know I can learn to use new CMC technologies when they come out.
__18. If a CMC isn't user friendly, I'm likely not to use it.

SKILLS

COORDINATION
__19. I know when and how to close down a topic of conversation in CMC dialogues.
__20. I manage the give and take of CMC interactions skillfully.
__21. I am skilled at timing when I send my responses to people who email me.
__22. I am skilled at prioritizing (triaging) my email traffic.

ATTENTIVENESS
__23. I ask questions of the other person in my CMC.
__24. I show concern for and interest in the person I'm conversing with in CMC.
__25. I can show compassion and empathy through the way I write emails.
__26. I take time to make sure my emails to others are uniquely adapted to the particular receiver I'm sending it to.

EXPRESSIVENESS
__27. I am very articulate and vivid in my CMC messages.
__28. I use a lot of the expressive symbols [e.g., ☺ for 'smile'] in my CMC messages.
__29. I try to use a lot of humor in my CMC messages.
__30. I am expressive in my CMC conversations.

COMPOSURE
__31. I display a lot of certainty in the way I write my CMC messages.
__32. I use an assertive style in my CMC writing.
__33. I have no trouble expressing my opinions forcefully on CMC.
__34. I make sure my objectives are emphasized in my CMC messages.
__35. My CMC messages are written in a confident style.
__36. I am skillful at revealing composure and self-confidence in my CMC interactions.

SELECTIVITY: I choose which medium (i.e., computer, phone, face-to-face, etc.) to communicate based on…
__37. … how quickly I need to get a message out to people.
__38. … how much benefit there would be to having the other(s) present face-to-face.
__39. … how lively the interaction needs to be.
__40. … how much access the person I need to communicate with has to the medium.
__41. … how much information is involved in the message I need to communicate.
__42. … how much access I have to the channel or medium.
__43. … how long I need people to hang on to or remember the message.
__44. … how many different uses and forms are needed (e.g., hardcopy, image processing, voice-mail, computer language, etc.)
__45. …how personal or intimate the information in the message is.
__46. …how quickly the receiver needs to react to the message.
__47. …the extent to which I need to get some "back and forth," "give and take," and interchange of ideas.
__48. …the extent to which I need some creative brainstorming.

APPROPRIATENESS
__49. I avoid saying things through that might offend someone.
__50. I pay as much attention to the WAY I say things as WHAT I say.
__51. I never say things that offend the other person.
__52. I am careful to make my comments and behaviors appropriate to the situation.

EFFECTIVENESS
__53. I generally get what I want out of interactions.
__54. I consistently achieve my goals in interactions.
__55. My interactions are effective in accomplishing what I set out to accomplish.
__56. I am effective in my conversations with others.

CLARITY
__57. I get my ideas across clearly in conversations with others.
__58. My comments are consistently accurate and clear.
__59. My messages are rarely misunderstood.
__60. I feel understood when I interact with others.

SATISFACTION
__61. I am generally satisfied with my communication encounters.
__62. I enjoy my interactions with others.
__63. I feel good about my conversations.
__64. I am generally pleased with my interactions.

ATTRACTIVENESS
__65. If I can engage someone in conversation, I can usually get them to like me.
__66. I come across in conversation as someone people would like to get to know.
__67. I make friends easily.
__68. People generally enjoy my company when interacting with me.

EFFICIENCY/PRODUCTIVITY
__69. I get a tremendous amount accomplished through CMC.
__70. My CMC interactions are more productive than my face-to-face interactions.
__71. I am more efficient using CMC than other forms of communication.
__72. CMC technologies are tremendous time-savers for my work.

GENERAL USAGE/EXPERIENCE
__73. I rely heavily upon my CMCs for getting me through each day.
__74. I use computer-mediated means of communication almost constantly.
__75. I can rarely go a week without any CMC interactions.
__76. I am a heavy user of computer-mediated communication.
__77. If I can use a computer for communicating, I tend to.

About the Author

Brian H. Spitzberg is a Professor in the School of Communication, San Diego State University. His research examines the assessment and conceptualization of interpersonal communication skills, as well as topics on the dark side of communication such as jealousy, coercion, violence, stalking, and cyberstalking.
Address: School of Communication, San Diego State University, San Diego, CA, 92182-4561 USA