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Computer Mediated Communication
Computer Mediated Communication Yuhua (Jake) Liang, Chapman University, Orange, CA, USA Joseph B Walther, Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore Ó 2015 Elsevier Ltd. All rights reserved.
Abstract Computer-mediated communication (CMC) involves sending messages through computer networks such as the Internet. Research on the social impacts of text-based CMC began with a cues-filtered-out perspective, highlighting the loss of social information due to the absence of face-to-face, nonverbal cues. More recent theories focus on how message senders exploit the CMC medium in order to create messages and relationships actively. A sender-receiver-message-channel-feedback model of communication reveals how CMC affects social dynamics.
Communication technologies have potentially altered the way human beings share information with one another. The ability to communicate by sending and receiving text information has been more readily available in recent history. Just as the Pony Express, the telegraph and the telephone enabled individuals to communicate across great distance, new communication technologies have again reinvented the available means of communication. Electronic communication technologies utilizing computers have refamiliarized our society with text-driven means of connecting with each other. Yet, despite the changes associated with historical text-based interpersonal media such as mail and phone, the rapid speed and other unique affordances of the Internet has sparked considerable interest in how computermediated communication (CMC) differs from traditional communication. The earliest research on CMC focused on the effects of new technology related to task performance outcomes. In the 1980s and 1990s, CMC consisted of electronic email and computer conferencing, chats, and electronic bulletin board systems hosting online forums. Research addressed the effects of those text-based communication systems not only on tasks, but also how the social dynamics and effects of the technology on users affected tasks or group performance. Today, with a greater variety of social media and expanded roles for their application, communication technology now plays an integral role in how people interact with one another across myriad types of social relationships. Communication technologies available today have increased the frequency, ubiquity, and impact of CMC. Individuals often work and interact with others via computers on a daily basis. People may access CMC through their mobile devices as well as computers. More complex and crowd-based systems exist today to provide new means of digital collaboration and online sharing. Social media technologies, such as Facebook and Twitter, provide highly accessible means of CMC by relating the content to the people we know. In addition to new enablement and accessibility, communication patterns today blend the use of offline and online channels across most of our personal and professional relationships (Ramirez and Zhang, 2007). Despite the mass proliferation and integration of CMC into our lives today, the delineation between CMC and
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other forms of communication remains useful and necessary in order to understand how technology affects communication processes. Even though CMC now hosts more multimodal channels in terms of photos, videos, and immersive graphical environments, text-based communication remains as a mainstay of how individuals exchange messages. Research developed on the basis of older textbased forms of CMC should continue to apply. As we develop an understanding of how CMC can affect communicators we can posit new questions as newer communication technologies such as Web 2.0 continue to expand the range of CMC. With that in mind, this article reviews several theoretical perspectives on CMC by focusing on the effects of CMC on those who use it, following the perspective of a basic communication model.
CMC: A Communication Perspective A basic model of communication aids in identifying the impact of CMC, the central components of which include senders, receivers, messages, feedback, and communication channel (see for review Walther, 1996). Senders initiate the exchange of information by articulating intentions into information to be conveyed to others. The message contains the information symbols representing the information to be exchanged. Senders deliver messages by using a communication channel, the vehicle that carries the message. Such vehicles include face-to-face communication, telephone, teleconference, Facebook posts, and electronic chats, among others. Receivers interpret the message and often provide a return message in the form of feedback. This feedback reverses the role of the senders and receivers as the cycle continues iteratively until the termination of the communication event. In addition to the capabilities of the CMC channel, CMC also occurs across different contexts. For example, Facebook’s social context alters how users may interpret and construct messages relative to email or other systems. When a Facebook user posts a status update, members of this person’s social network may read the message in light of past interactions with that user. On the other hand, messages exchanged on a company or organization’s office chat system likely result in a different interpretive framework. Employees may experience
International Encyclopedia of the Social & Behavioral Sciences, 2nd edition, Volume 4
http://dx.doi.org/10.1016/B978-0-08-097086-8.95090-6
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more reluctance in sharing social activities outside of the workplace on company websites as opposed to their friends and family via Facebook. New communication technologies challenge existing theoretical perspectives. Early views of CMC focused on comparing the ability of the communication channel to those in faceto-face communication and/or other forms of CMC. Theoretical developments that followed offered a different view of CMC. Instead of focusing on the limiting constraints of the communication channel, these developments focused on how users can adapt to CMC to convey messages. We begin with an overview of the earlier theoretical view of CMC based on channel characteristics.
Cues-Filtered-Out Theories Culnan and Markus (1987) first described a class of CMC theories as adopting a cues-filtered-out approach. The major contention in these theories maintains that CMC constraints the symbol systems that are available in the communication process, and thereby limits the meaning that users are able to exchange. Because CMC is primarily text-based, it lacks nonverbal cues. These theories assumed a relationship between the restricted cues that the channels offered and a commensurate restriction in senders’ abilities to convey certain kinds of messages. There was less focus on the senders and receivers in terms of their potential adaptation of messages to alternative channels. Several particular theories typify the cues-filtered-out perspective.
Social Presence Theory The first theory applied to CMC that reflected a cues-filtered-out perspective is social presence theory. Short et al. (1976) conceptualized that various communication systems differ in the availability of cue systems. Short et al. also claimed that the decrease of cues corresponded to a decrease in social presence between communicators. Although the theory originally focused on telecommunication systems, it was applied to CMC in the 1980s and 1990s. The restriction of cue systems was suggested to impact the degree of social information a system could convey. Therefore, information about individuals’ character and personality, and their interpersonal warmth and ease would be unlikely to be exchanged effectively without nonverbal cues, from a social presence perspective.
Media Richness Theory Social information differs from more instrumental forms of information, for which certain other cues-filtered-out theories, media richness theory in particular (Daft and Lengel, 1984, 1986), suggest that “leaner” media (without nonverbal cues) may be more efficient. For instance, CMC may suffice when one person needs to tell another person the date for an event. On the other hand, if an individual wished to get to know another person’s character or personality – characteristics which nonverbal cues might more efficiently convey – social presence and media richness theories suggest that CMC would denude
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the quality of information due to the lack of nonverbal cues to express socioemotional content. Media richness theory focused on how organizations can utilize different types of communication channels to deal with decision-making contexts. Daft and Lengel (1984) attempted to provide a model for how different communication channels (e.g., memos, letters, chats, telephone conversations, and face-to-face interactions) rank in their abilities to reduce the equivocality managers experience during decision making. Equivocality refers to the ambiguity that arises from the presence of multiple, possibly conflicting interpretations. For example, a decision regarding whether a new policy should be adopted should evoke high equivocality. Such a context involves discussions among various managers and different interpretations regarding the consequences of the policy implementation. These researchers contended that the ability of the communication channel to manage equivocality depended on information richness, which is comprised of (1) feedback speed or the rapidity of feedback, (2) multiple cues or the number of cues supported by the communication system, (3) language variety or the range of meaning that can be conveyed with language, and (4) personal focus or the ability of the communication to convey personal feelings and emotions (Daft et al., 1987). According to the media richness view, faceto-face communication would rank as the richest channel whereas other forms of mediated communication would be leaner (Daft et al., 1987). Face-to-face communication contains fast feedback, the greatest number of cues, the use of natural language, and the ability to adapt to individuals. On the other hand, CMC, such as chats and emails, would rank lower due to the lack of some richness criteria. It is regarded as a leaner group of channels. Media richness theory argued that the best communication performance occurs as a function of matching the equivocality of the communication task to the richness of the communication channel. Specifically, high equivocality would require high information richness, and vice versa. For instance, managers attempting to make a policy decision require discussion and interpretation among multiple perspectives, thus face-to-face communication would be ideal. Alternatively, sharing accounting information or other objective data does not elicit a high degree of equivocality, meaning that a lean channel such as email would actually be more ideal in this context.
Empirical Findings Both social presence theory and media richness theory provide a fairly intuitive understanding of CMC. The simplicity of treating different CMC categorically based on the absence of nonverbal cues is transparent and simple. Perhaps due to such an appeal, numerous investigations followed a cues-filteredout approach in both organizational and interpersonal contexts. However, the empirical support has been generally mixed. Social presence theory has received numerous critiques and challenges for the oversimplification explanation of CMC in a social context (Lea and Spears, 1992; Walther, 1992). In short, these critiques centered on challenging the assumptions and artifacts present in social presence work. Media richness
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theory has also been challenged in from multiple angles. First, the original study did not directly test the theoretical proposition laid out by its authors. The empirical support used to substantiate the theory’s formulation involved asking managers what communication channel they would select in a number of communication contexts that differed in equivocality. Daft et al. (1987) found a positive correlation between how well the managers selected the communication channel and the manager’s actual performance evaluations. This correlation did not test the theoretical proposition that using various communication channels resulted in the best decision-making outcome, given situations that vary in equivocality. Dennis and Kinney (1998) experimentally tested media richness theory and failed to find supporting evidence. These researchers found that richness led to differences in the time that it would take to complete a task. However, richness did not affect decision quality. In short, the critiques and contradictory evidence limit the viability of the cues-filteredout approach to understanding CMC. Despite the critiques and problems associated with cuesfiltered-out approaches, this view of CMC continues to perpetuate in recent studies of new media (see for review Walther, 2011). Adopting a cues-filtered-out approach often hinders the advances possible in the study of CMC. Fortunately, alternative theoretical views focus on how CMC integrates factors beyond those in the communication channel alone.
Social Identity Model of Deindividuation Effects The social identity model of deindividuation effects, or SIDE model (Lea and Spears, 1992), shares some similarities with the other cues-filter-out theories. Specifically, SIDE also assumes that the absence of nonverbal cues limits the transmission of interpersonal information online. However, unlike other cues-filtered-out approaches, the SIDE offers a mechanism for online communication based on visual anonymity and social identification. Visual anonymity occurs when communicators utilize text-based communication where no visual information about each other is available. Under such a condition, communicators deindividuate and lose a sense of self-awareness. If they identify themselves with a salient social group, they will likely follow the behaviors of that social group. The following scenario exemplifies a scenario for how SIDE may function in CMC. Assume that a college student reads and writes responses on a political forum. If the forum is text-based, the student should remain visually anonymous to others on the forum, as well as others to the student. The student is able to garner information about others on the forum and realizes that some of the forum participants are also students at the same university. If the student identifies with the ingroup of students from the same university, he or she should orient toward the behavior of those from the same institution (e.g., evaluate them as more attractive, follow the recommendations advocated). On the other hand, if the student realizes that some of the other contributors on the same forum are from a rival institution, he or she may regard these people as out-group members. The student is likely to evaluate these out-group members as less attractive
and be less likely to follow any recommendations advocated by those members. The SIDE model’s parsimonious explanation of visually anonymous CMC led to a wide following. The theory has even been applied to understand the effect of CMC in interpersonal contexts: In the case of visually anonymous romantic partners who may have met online, SIDE offers an interesting interpretation for their relational development. An application of the SIDE suggests that romantic communication and attraction toward partners result due to the social identification they feel toward salient group identities. According to SIDE, the attraction does not develop out of interpersonal processes but group identification processes alone (Lea and Spears, 1995). Taken together, the cues-filtered out approaches to CMC provide a limited understanding of how people communicate. The primary assumption that text-based communication can only convey a certain quantity or form of meaning ignores any possibilities of relational development or transformative properties using CMC. In the case of SIDE, the prediction that social identification with group members would lead to adherence to group behavior also assumed that visual anonymity and text-based communication restrict or discourage users from conveying personal and interpersonal information. The next few of theoretical perspectives focus more on the interpersonal capabilities of CMC. In particular, these perspectives emphasize communicators’ ability to utilize CMC in such a way as to provide meaning, to detect and foster personal impressions, and develop relational communication that approximates, or even exceeds, the level of relational regard that is typical in face-to-face communication.
Theories of Interpersonal Adaptation A fundamental difference between cues-filtered-out approaches and theories described below can be understood from the communication model. Cues-filtered-out approaches focus on the channel primarily, with the exception of SIDE which also focuses on receivers’ social identification. Instead, the theoretical frameworks of interpersonal adaptation and exploitation of media posit an understanding of CMC through all components of the communication model, raising in prominence the role of the sender and the sender’s active creation of messages and channels. This approach to understanding CMC paints a picture of how communicators can take advantage of all communication elements to share meaning.
Social Information Processing Theory The social information processing (SIP) theory (Walther, 1992) assumes that individuals aim to develop interpersonal impressions and relations with others. It proposes that when the communication channel limits the cues available to communicators, as is the case using text-based CMC, individuals will utilize the available cues in that channel to share their desired meaning. In particular, communicators primarily utilize the content of the written language (e.g., the choice and style of words) to encode and decode information from others.
Computer Mediated Communication
In addition to CMC adaptation from a sender’s standpoint, SIP supposes that the CMC channel alters the rate of social information exchange compared to face-to-face communication. In other words, to develop to the same level of relationship, communicators who use CMC would require more time than those in face-to-face communication. This rate difference originates from the diminished information available in text-based CMC as opposed to face-to-face communication. Even as senders encode messages by adapting to the cues and meaning available in CMC, the communication takes more time to accrue the same meaning as those in face-to-face communication. However, it is important to note that the rate difference does not equate to a superiority or inferiority of CMC when compared to the face-to-face counterpart. Instead, social information simply needs more time to accumulate and render effects on relationships in CMC.
The Hyperpersonal Model of CMC The hyperpersonal model of CMC (Walther, 1996) takes a step beyond SIP theory. Specifically, the hyperpersonal model contends that CMC may aid in the development of interpersonal relationships that even surpass those in face-to-face communication. Such a process entails a series of theoretical propositions that relate to (1) how receivers may process CMC information, (2) how senders may encode messages, (3) characteristics of the communication channel, and (4) feedback. These propositions coalesce to describe a CMC process that involves all components of the communication model.
Receiver Effects A receiver may experience exaggerated perceptions of the message sender in CMC. Since a receiver does not have the cues present in face-to-face communication, the receiver has to fill the void by creating impressions regarding the sender. When initial cues lead to positive first impression, impression development may then involve idealization, where the receiver bestows characteristics about the sender preferentially. This articulation originated from the notion of social identification to group identity in SIDE theory. Newer accounts of the hyperpersonal model suggests that individual stereotypes, not just those based on common social categories, may also activate heightened receiver impressions (Walther, 2006).
Sender Effects With a text-based CMC in mind, communicators can selectively present aspects of themselves online. As a result, they can manage which aspects of themselves to present to others, with an underlying goal to create a favorable impression in the other communication partner. Of course, individuals can choose to disclose negative personal information; however, the lack of nonverbal cues in CMC actually minimizes the nonverbal behavior that might damage positive interpersonal impressions (e.g., poor eye contact, body postures) in faceto-face communication. As a result, CMC senders can more easily select aspect of themselves to present to their partners to elicit favorable responses.
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Channel Not only can senders selectively self-present, their ability to do so is enhanced by the communication channel. Several aspects of CMC facilitate message construction. For instance, in the case of asynchronous CMC, both the sender and the receiver can utilize time to construct the message and feedback. Unlike face-to-face communication where the feedback between communicators is more immediate, a CMC sender and a CMC receiver have time to write the message, edit that message, or even delete and rewrite the message. The use of time and editing leads to more positive and affectionate messages (see for review Walther, 2011).
Feedback According to the former three components of the hyperpersonal model, the sender may selectively self-present to garner positive impressions, the receiver may idealize the sender, while both the sender and the receiver may capitalize on the CMC channel to construct favorable messages. Based on these enhancements, the feedback system created between the sender and the receiver should contribute to a continuous elevation of positive impression as they communicate with each other. In other words, the feedback system in CMC should enhance the interpersonal dynamics at play and intensify the effects iteratively over time. A synthesis of all four hyperpersonal components illustrates a communication dynamic where the positive impressions of the CMC communicators intensify over time. The model points the possibility where such intensification may exceed those experienced in face-to-face communication. Both SIP theory and the hyperpersonal model challenge the limited views provided by the cues-filtered-out approaches to CMC. Moreover, the theories of adaptation of exploitation of media paint CMC as an interactional landscape where users adapt and appropriate all available means in the communication process to reach affinity goals. Although the domain of these theories resides primarily in the interpersonal context, the theories’ application and interpretation suggest that communication should be understood from the communicator’s standpoint rather than the technology or the channel.
Online Information Evaluation Warranting In addition to cyclical communication processes posited by theories of interpersonal adaptation and exploitation of media, some recent theoretical concepts examine how individuals may make sense of information they receive online. Online communication may involve the information individuals disclose to each other. Individuals often evaluate the validity of information about another person online, also known as warranting (Walther and Parks, 2002). The communication technology today provides quick access to information. Online users also have access to a lot of information about others. For example, online users may share a lot of personal information on their online dating profiles including interests, religious views, hobbies, among others. The warranting idea suggests that information presented online may lead to a suspicion of
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possible distortions through selective self-presentation, such as the sender effect specified by the hyperpersonal model. For example, information on dating websites may show both distorted physical (weight/height) and psychological (hobbies) characteristics. The warranting concept argues that such type of distortion is less likely to occur when two communicators have access to each other’s social network. Specifically, when one communication partner’s social circle is available, one partner can hold the other responsible for the content of the self-disclosure and verify that content. Based on warranting, information that is more likely to relate to a communication partner’s social network is less likely to be seen as distorted. Warranting is useful in predicting how communicators may judge the social information provided by others online.
Participatory Websites The CMC available today has dramatically changed from the early text-based forms. Most online communication occurs via websites that feature some social information from other users. These types of participatory websites, known as Web 2.0, complicate the theoretical concepts for understanding the underlying communication dynamics at play. Moreover, these social websites juxtapose messages from various sources. An original author of some Web content may receive comments and evaluation from other users regarding that content. From a communication perspective, information regarding the sender, receiver, message, feedback, and context may blend together in a single webpage. The additional usergenerated content may serve to modify how other readers may evaluate the content advocated by the original author, the original author as a source, others who comment on the source, as well as the content of the comments advocated by others. This following example illustrates the complexity of understanding Web 2.0. Suppose that a product reviewer posts a positive product review on Amazon.com. Assuming that the review was meant to advocate to other readers for purchasing a particular product, other readers may compose comments on the review. If other readers write positive comments regarding the review, then those who read the original review and corresponding comments may regard the product as positive overall. However, if the review received negative comments that do not support what the review advocates, readers of the reviews and the comments that follow have to make sense of both positive and negative information. To complicate matter even more, Amazon.com reviewers and commenters may be rated in terms of how helpful they are. These types of information juxtapose against one another as the reader may review them on a single website. Walther and Jang (2012) offered a conceptual foundation for defining the various sources available on Web 2.0 sites. They proposed four elements including proprietor content, usergenerated content, deliberate aggregate user representations, and incidental aggregate user representations.
Proprietor Content Proprietor content relates to the message composed by the primary author or the proprietor of a webpage. The proprietor
has controls over message that he or she composes. The proprietor may edit that message (e.g., deleting a Facebook post). The message may include videos, text, and/or pictures. Furthermore, these forms of messages may operate in combination. A Facebook picture may accompany the written post in text. Examples of proprietor content include YouTube videos, Amazon.com reviews, Facebook profiles, among others.
User-Generated Content User-generated content (UGC) relates to the messages that other users contribute. This content does not originate from the proprietor, but instead, from those who compose content in response to the proprietor content. UGC differentiates Web 2.0 from traditional websites. Unlike traditional websites (e.g., a webpage that does not allow users to write comments), Web 2.0 displays UGC alongside the proprietor content. Examples of UGC include comments responding to a Facebook post, comments on product reviews (comments written in response to an online news article).
Aggregated User Representations Web 2.0 systems also allow users to leave evaluations of others’ content. These evaluations may relate to proprietor content, as well as UGC. Web 2.0 systems often encourage users to rate or vote on the content produced by others. Then, the system aggregates the ratings for others to view. The aggregated ratings take the form of some statistics or figures. Examples of these representations include the number of stars, total votes, usefulness votes, helpfulness ratios, among others. To delineate among the different types of user representations, there are deliberate and incidental aggregate user representations. Deliberate aggregate user representations include responses generated from directly requesting those responses from users. For instance, after displaying an opinion from a user, the Web 2.0 system may solicit readers to rate if that opinion was useful or not useful (e.g., 1 to 5 stars). An example of deliberate representation may include ratings of review helpfulness. Amazon.com displays the accumulated ratings of helpfulness in the form of a ratio (e.g., 40 out of 41 people found the review helpful). In contrast, incidental aggregate user representations include information captured by Web 2.0 systems. In particular, these representations do not reflect behaviors that users would like to express, but instead, they are computed by the Web 2.0 system and displayed with other information. Examples of these representations include the number of Facebook friends, number of views on a YouTube video, the timestamp of a particular comment or review, among others. These representations offer a unique persuasive quality in that online users have no control over them. As a result, they may serve to aid certain aspects of self-presentations from a warranting perspective.
Participatory Websites and Juxtaposition among Sources Participatory websites create unique theoretical challenges for CMC. Although the theoretical terms expressed previously aid in defining the various conceptual components involved in Web 2.0, they do not offer a set of theoretical
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propositions regarding the relationships among the concepts. From a communication perspective, the model elements of the sender, receiver, message, context, and feedback also offer little explanatory utility as these components mix to serve multiple roles in Web 2.0. For instance, a message proprietor may respond to UGC and create a conversation between a proprietor and a commenter. At the same time, other users contribute to this dynamic through rating both the proprietor content and/or the UGC. When the Web 2.0 system displays all these contents simultaneously, how do other readers process that information and continue in the participatory process by adding or rating the existing content? What if more than one commenter is involved? This question typifies the theoretical challenge in the study of CMC as new technology enable online communicators to interact at such a convergent level across multiple information sources and ratings.
Summary and Future Direction The current review began with an explanation of the communication perspective and elements in the communication model. With this perspective in mind, we reviewed a few of the theories involved in understanding CMC. The cues-filtered-out approaches assumed CMC’s lack of nonverbal cues limited communication. On the other hand, theories of interpersonal adaption and exploitation of media posit a more interactive process that may match and/or exceed face to face. Finally, the conceptual framework for understanding participatory websites provides a glimpse of the complexity and challenge of theory development. As research incrementally increases our understanding of CMC, technology is also on the forefront of altering the landscape of digital interaction. Web 2.0 site continue to modify both interface as well as the type of information available to users.
See also: Audiences, Media; Information Society; Social Media.
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Abstract Computer-mediated communication (CMC) involves sending messages through computer networks such as the Internet. Research on the social impacts of text-based CMC began with a cues-filtered-out perspective, highlighting the loss of social information due to the absence of face-to-face, nonverbal cues. More recent theories focus on how message senders exploit the CMC medium in order to create messages and relationships actively. A sender-receiver-message-channel-feedback model of communication reveals how CMC affects social dynamics.
Communication technologies have potentially altered the way human beings share information with one another. The ability to communicate by sending and receiving text information has been more readily available in recent history. Just as the Pony Express, the telegraph and the telephone enabled individuals to communicate across great distance, new communication technologies have again reinvented the available means of communication. Electronic communication technologies utilizing computers have refamiliarized our society with text-driven means of connecting with each other. Yet, despite the changes associated with historical text-based interpersonal media such as mail and phone, the rapid speed and other unique affordances of the Internet has sparked considerable interest in how computermediated communication (CMC) differs from traditional communication. The earliest research on CMC focused on the effects of new technology related to task performance outcomes. In the 1980s and 1990s, CMC consisted of electronic email and computer conferencing, chats, and electronic bulletin board systems hosting online forums. Research addressed the effects of those text-based communication systems not only on tasks, but also how the social dynamics and effects of the technology on users affected tasks or group performance. Today, with a greater variety of social media and expanded roles for their application, communication technology now plays an integral role in how people interact with one another across myriad types of social relationships. Communication technologies available today have increased the frequency, ubiquity, and impact of CMC. Individuals often work and interact with others via computers on a daily basis. People may access CMC through their mobile devices as well as computers. More complex and crowd-based systems exist today to provide new means of digital collaboration and online sharing. Social media technologies, such as Facebook and Twitter, provide highly accessible means of CMC by relating the content to the people we know. In addition to new enablement and accessibility, communication patterns today blend the use of offline and online channels across most of our personal and professional relationships (Ramirez and Zhang, 2007). Despite the mass proliferation and integration of CMC into our lives today, the delineation between CMC and
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other forms of communication remains useful and necessary in order to understand how technology affects communication processes. Even though CMC now hosts more multimodal channels in terms of photos, videos, and immersive graphical environments, text-based communication remains as a mainstay of how individuals exchange messages. Research developed on the basis of older textbased forms of CMC should continue to apply. As we develop an understanding of how CMC can affect communicators we can posit new questions as newer communication technologies such as Web 2.0 continue to expand the range of CMC. With that in mind, this article reviews several theoretical perspectives on CMC by focusing on the effects of CMC on those who use it, following the perspective of a basic communication model.
CMC: A Communication Perspective A basic model of communication aids in identifying the impact of CMC, the central components of which include senders, receivers, messages, feedback, and communication channel (see for review Walther, 1996). Senders initiate the exchange of information by articulating intentions into information to be conveyed to others. The message contains the information symbols representing the information to be exchanged. Senders deliver messages by using a communication channel, the vehicle that carries the message. Such vehicles include face-to-face communication, telephone, teleconference, Facebook posts, and electronic chats, among others. Receivers interpret the message and often provide a return message in the form of feedback. This feedback reverses the role of the senders and receivers as the cycle continues iteratively until the termination of the communication event. In addition to the capabilities of the CMC channel, CMC also occurs across different contexts. For example, Facebook’s social context alters how users may interpret and construct messages relative to email or other systems. When a Facebook user posts a status update, members of this person’s social network may read the message in light of past interactions with that user. On the other hand, messages exchanged on a company or organization’s office chat system likely result in a different interpretive framework. Employees may experience
International Encyclopedia of the Social & Behavioral Sciences, 2nd edition, Volume 4
http://dx.doi.org/10.1016/B978-0-08-097086-8.95090-6
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more reluctance in sharing social activities outside of the workplace on company websites as opposed to their friends and family via Facebook. New communication technologies challenge existing theoretical perspectives. Early views of CMC focused on comparing the ability of the communication channel to those in faceto-face communication and/or other forms of CMC. Theoretical developments that followed offered a different view of CMC. Instead of focusing on the limiting constraints of the communication channel, these developments focused on how users can adapt to CMC to convey messages. We begin with an overview of the earlier theoretical view of CMC based on channel characteristics.
Cues-Filtered-Out Theories Culnan and Markus (1987) first described a class of CMC theories as adopting a cues-filtered-out approach. The major contention in these theories maintains that CMC constraints the symbol systems that are available in the communication process, and thereby limits the meaning that users are able to exchange. Because CMC is primarily text-based, it lacks nonverbal cues. These theories assumed a relationship between the restricted cues that the channels offered and a commensurate restriction in senders’ abilities to convey certain kinds of messages. There was less focus on the senders and receivers in terms of their potential adaptation of messages to alternative channels. Several particular theories typify the cues-filtered-out perspective.
Social Presence Theory The first theory applied to CMC that reflected a cues-filtered-out perspective is social presence theory. Short et al. (1976) conceptualized that various communication systems differ in the availability of cue systems. Short et al. also claimed that the decrease of cues corresponded to a decrease in social presence between communicators. Although the theory originally focused on telecommunication systems, it was applied to CMC in the 1980s and 1990s. The restriction of cue systems was suggested to impact the degree of social information a system could convey. Therefore, information about individuals’ character and personality, and their interpersonal warmth and ease would be unlikely to be exchanged effectively without nonverbal cues, from a social presence perspective.
Media Richness Theory Social information differs from more instrumental forms of information, for which certain other cues-filtered-out theories, media richness theory in particular (Daft and Lengel, 1984, 1986), suggest that “leaner” media (without nonverbal cues) may be more efficient. For instance, CMC may suffice when one person needs to tell another person the date for an event. On the other hand, if an individual wished to get to know another person’s character or personality – characteristics which nonverbal cues might more efficiently convey – social presence and media richness theories suggest that CMC would denude
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the quality of information due to the lack of nonverbal cues to express socioemotional content. Media richness theory focused on how organizations can utilize different types of communication channels to deal with decision-making contexts. Daft and Lengel (1984) attempted to provide a model for how different communication channels (e.g., memos, letters, chats, telephone conversations, and face-to-face interactions) rank in their abilities to reduce the equivocality managers experience during decision making. Equivocality refers to the ambiguity that arises from the presence of multiple, possibly conflicting interpretations. For example, a decision regarding whether a new policy should be adopted should evoke high equivocality. Such a context involves discussions among various managers and different interpretations regarding the consequences of the policy implementation. These researchers contended that the ability of the communication channel to manage equivocality depended on information richness, which is comprised of (1) feedback speed or the rapidity of feedback, (2) multiple cues or the number of cues supported by the communication system, (3) language variety or the range of meaning that can be conveyed with language, and (4) personal focus or the ability of the communication to convey personal feelings and emotions (Daft et al., 1987). According to the media richness view, faceto-face communication would rank as the richest channel whereas other forms of mediated communication would be leaner (Daft et al., 1987). Face-to-face communication contains fast feedback, the greatest number of cues, the use of natural language, and the ability to adapt to individuals. On the other hand, CMC, such as chats and emails, would rank lower due to the lack of some richness criteria. It is regarded as a leaner group of channels. Media richness theory argued that the best communication performance occurs as a function of matching the equivocality of the communication task to the richness of the communication channel. Specifically, high equivocality would require high information richness, and vice versa. For instance, managers attempting to make a policy decision require discussion and interpretation among multiple perspectives, thus face-to-face communication would be ideal. Alternatively, sharing accounting information or other objective data does not elicit a high degree of equivocality, meaning that a lean channel such as email would actually be more ideal in this context.
Empirical Findings Both social presence theory and media richness theory provide a fairly intuitive understanding of CMC. The simplicity of treating different CMC categorically based on the absence of nonverbal cues is transparent and simple. Perhaps due to such an appeal, numerous investigations followed a cues-filteredout approach in both organizational and interpersonal contexts. However, the empirical support has been generally mixed. Social presence theory has received numerous critiques and challenges for the oversimplification explanation of CMC in a social context (Lea and Spears, 1992; Walther, 1992). In short, these critiques centered on challenging the assumptions and artifacts present in social presence work. Media richness
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theory has also been challenged in from multiple angles. First, the original study did not directly test the theoretical proposition laid out by its authors. The empirical support used to substantiate the theory’s formulation involved asking managers what communication channel they would select in a number of communication contexts that differed in equivocality. Daft et al. (1987) found a positive correlation between how well the managers selected the communication channel and the manager’s actual performance evaluations. This correlation did not test the theoretical proposition that using various communication channels resulted in the best decision-making outcome, given situations that vary in equivocality. Dennis and Kinney (1998) experimentally tested media richness theory and failed to find supporting evidence. These researchers found that richness led to differences in the time that it would take to complete a task. However, richness did not affect decision quality. In short, the critiques and contradictory evidence limit the viability of the cues-filteredout approach to understanding CMC. Despite the critiques and problems associated with cuesfiltered-out approaches, this view of CMC continues to perpetuate in recent studies of new media (see for review Walther, 2011). Adopting a cues-filtered-out approach often hinders the advances possible in the study of CMC. Fortunately, alternative theoretical views focus on how CMC integrates factors beyond those in the communication channel alone.
Social Identity Model of Deindividuation Effects The social identity model of deindividuation effects, or SIDE model (Lea and Spears, 1992), shares some similarities with the other cues-filter-out theories. Specifically, SIDE also assumes that the absence of nonverbal cues limits the transmission of interpersonal information online. However, unlike other cues-filtered-out approaches, the SIDE offers a mechanism for online communication based on visual anonymity and social identification. Visual anonymity occurs when communicators utilize text-based communication where no visual information about each other is available. Under such a condition, communicators deindividuate and lose a sense of self-awareness. If they identify themselves with a salient social group, they will likely follow the behaviors of that social group. The following scenario exemplifies a scenario for how SIDE may function in CMC. Assume that a college student reads and writes responses on a political forum. If the forum is text-based, the student should remain visually anonymous to others on the forum, as well as others to the student. The student is able to garner information about others on the forum and realizes that some of the forum participants are also students at the same university. If the student identifies with the ingroup of students from the same university, he or she should orient toward the behavior of those from the same institution (e.g., evaluate them as more attractive, follow the recommendations advocated). On the other hand, if the student realizes that some of the other contributors on the same forum are from a rival institution, he or she may regard these people as out-group members. The student is likely to evaluate these out-group members as less attractive
and be less likely to follow any recommendations advocated by those members. The SIDE model’s parsimonious explanation of visually anonymous CMC led to a wide following. The theory has even been applied to understand the effect of CMC in interpersonal contexts: In the case of visually anonymous romantic partners who may have met online, SIDE offers an interesting interpretation for their relational development. An application of the SIDE suggests that romantic communication and attraction toward partners result due to the social identification they feel toward salient group identities. According to SIDE, the attraction does not develop out of interpersonal processes but group identification processes alone (Lea and Spears, 1995). Taken together, the cues-filtered out approaches to CMC provide a limited understanding of how people communicate. The primary assumption that text-based communication can only convey a certain quantity or form of meaning ignores any possibilities of relational development or transformative properties using CMC. In the case of SIDE, the prediction that social identification with group members would lead to adherence to group behavior also assumed that visual anonymity and text-based communication restrict or discourage users from conveying personal and interpersonal information. The next few of theoretical perspectives focus more on the interpersonal capabilities of CMC. In particular, these perspectives emphasize communicators’ ability to utilize CMC in such a way as to provide meaning, to detect and foster personal impressions, and develop relational communication that approximates, or even exceeds, the level of relational regard that is typical in face-to-face communication.
Theories of Interpersonal Adaptation A fundamental difference between cues-filtered-out approaches and theories described below can be understood from the communication model. Cues-filtered-out approaches focus on the channel primarily, with the exception of SIDE which also focuses on receivers’ social identification. Instead, the theoretical frameworks of interpersonal adaptation and exploitation of media posit an understanding of CMC through all components of the communication model, raising in prominence the role of the sender and the sender’s active creation of messages and channels. This approach to understanding CMC paints a picture of how communicators can take advantage of all communication elements to share meaning.
Social Information Processing Theory The social information processing (SIP) theory (Walther, 1992) assumes that individuals aim to develop interpersonal impressions and relations with others. It proposes that when the communication channel limits the cues available to communicators, as is the case using text-based CMC, individuals will utilize the available cues in that channel to share their desired meaning. In particular, communicators primarily utilize the content of the written language (e.g., the choice and style of words) to encode and decode information from others.
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In addition to CMC adaptation from a sender’s standpoint, SIP supposes that the CMC channel alters the rate of social information exchange compared to face-to-face communication. In other words, to develop to the same level of relationship, communicators who use CMC would require more time than those in face-to-face communication. This rate difference originates from the diminished information available in text-based CMC as opposed to face-to-face communication. Even as senders encode messages by adapting to the cues and meaning available in CMC, the communication takes more time to accrue the same meaning as those in face-to-face communication. However, it is important to note that the rate difference does not equate to a superiority or inferiority of CMC when compared to the face-to-face counterpart. Instead, social information simply needs more time to accumulate and render effects on relationships in CMC.
The Hyperpersonal Model of CMC The hyperpersonal model of CMC (Walther, 1996) takes a step beyond SIP theory. Specifically, the hyperpersonal model contends that CMC may aid in the development of interpersonal relationships that even surpass those in face-to-face communication. Such a process entails a series of theoretical propositions that relate to (1) how receivers may process CMC information, (2) how senders may encode messages, (3) characteristics of the communication channel, and (4) feedback. These propositions coalesce to describe a CMC process that involves all components of the communication model.
Receiver Effects A receiver may experience exaggerated perceptions of the message sender in CMC. Since a receiver does not have the cues present in face-to-face communication, the receiver has to fill the void by creating impressions regarding the sender. When initial cues lead to positive first impression, impression development may then involve idealization, where the receiver bestows characteristics about the sender preferentially. This articulation originated from the notion of social identification to group identity in SIDE theory. Newer accounts of the hyperpersonal model suggests that individual stereotypes, not just those based on common social categories, may also activate heightened receiver impressions (Walther, 2006).
Sender Effects With a text-based CMC in mind, communicators can selectively present aspects of themselves online. As a result, they can manage which aspects of themselves to present to others, with an underlying goal to create a favorable impression in the other communication partner. Of course, individuals can choose to disclose negative personal information; however, the lack of nonverbal cues in CMC actually minimizes the nonverbal behavior that might damage positive interpersonal impressions (e.g., poor eye contact, body postures) in faceto-face communication. As a result, CMC senders can more easily select aspect of themselves to present to their partners to elicit favorable responses.
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Channel Not only can senders selectively self-present, their ability to do so is enhanced by the communication channel. Several aspects of CMC facilitate message construction. For instance, in the case of asynchronous CMC, both the sender and the receiver can utilize time to construct the message and feedback. Unlike face-to-face communication where the feedback between communicators is more immediate, a CMC sender and a CMC receiver have time to write the message, edit that message, or even delete and rewrite the message. The use of time and editing leads to more positive and affectionate messages (see for review Walther, 2011).
Feedback According to the former three components of the hyperpersonal model, the sender may selectively self-present to garner positive impressions, the receiver may idealize the sender, while both the sender and the receiver may capitalize on the CMC channel to construct favorable messages. Based on these enhancements, the feedback system created between the sender and the receiver should contribute to a continuous elevation of positive impression as they communicate with each other. In other words, the feedback system in CMC should enhance the interpersonal dynamics at play and intensify the effects iteratively over time. A synthesis of all four hyperpersonal components illustrates a communication dynamic where the positive impressions of the CMC communicators intensify over time. The model points the possibility where such intensification may exceed those experienced in face-to-face communication. Both SIP theory and the hyperpersonal model challenge the limited views provided by the cues-filtered-out approaches to CMC. Moreover, the theories of adaptation of exploitation of media paint CMC as an interactional landscape where users adapt and appropriate all available means in the communication process to reach affinity goals. Although the domain of these theories resides primarily in the interpersonal context, the theories’ application and interpretation suggest that communication should be understood from the communicator’s standpoint rather than the technology or the channel.
Online Information Evaluation Warranting In addition to cyclical communication processes posited by theories of interpersonal adaptation and exploitation of media, some recent theoretical concepts examine how individuals may make sense of information they receive online. Online communication may involve the information individuals disclose to each other. Individuals often evaluate the validity of information about another person online, also known as warranting (Walther and Parks, 2002). The communication technology today provides quick access to information. Online users also have access to a lot of information about others. For example, online users may share a lot of personal information on their online dating profiles including interests, religious views, hobbies, among others. The warranting idea suggests that information presented online may lead to a suspicion of
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possible distortions through selective self-presentation, such as the sender effect specified by the hyperpersonal model. For example, information on dating websites may show both distorted physical (weight/height) and psychological (hobbies) characteristics. The warranting concept argues that such type of distortion is less likely to occur when two communicators have access to each other’s social network. Specifically, when one communication partner’s social circle is available, one partner can hold the other responsible for the content of the self-disclosure and verify that content. Based on warranting, information that is more likely to relate to a communication partner’s social network is less likely to be seen as distorted. Warranting is useful in predicting how communicators may judge the social information provided by others online.
Participatory Websites The CMC available today has dramatically changed from the early text-based forms. Most online communication occurs via websites that feature some social information from other users. These types of participatory websites, known as Web 2.0, complicate the theoretical concepts for understanding the underlying communication dynamics at play. Moreover, these social websites juxtapose messages from various sources. An original author of some Web content may receive comments and evaluation from other users regarding that content. From a communication perspective, information regarding the sender, receiver, message, feedback, and context may blend together in a single webpage. The additional usergenerated content may serve to modify how other readers may evaluate the content advocated by the original author, the original author as a source, others who comment on the source, as well as the content of the comments advocated by others. This following example illustrates the complexity of understanding Web 2.0. Suppose that a product reviewer posts a positive product review on Amazon.com. Assuming that the review was meant to advocate to other readers for purchasing a particular product, other readers may compose comments on the review. If other readers write positive comments regarding the review, then those who read the original review and corresponding comments may regard the product as positive overall. However, if the review received negative comments that do not support what the review advocates, readers of the reviews and the comments that follow have to make sense of both positive and negative information. To complicate matter even more, Amazon.com reviewers and commenters may be rated in terms of how helpful they are. These types of information juxtapose against one another as the reader may review them on a single website. Walther and Jang (2012) offered a conceptual foundation for defining the various sources available on Web 2.0 sites. They proposed four elements including proprietor content, usergenerated content, deliberate aggregate user representations, and incidental aggregate user representations.
Proprietor Content Proprietor content relates to the message composed by the primary author or the proprietor of a webpage. The proprietor
has controls over message that he or she composes. The proprietor may edit that message (e.g., deleting a Facebook post). The message may include videos, text, and/or pictures. Furthermore, these forms of messages may operate in combination. A Facebook picture may accompany the written post in text. Examples of proprietor content include YouTube videos, Amazon.com reviews, Facebook profiles, among others.
User-Generated Content User-generated content (UGC) relates to the messages that other users contribute. This content does not originate from the proprietor, but instead, from those who compose content in response to the proprietor content. UGC differentiates Web 2.0 from traditional websites. Unlike traditional websites (e.g., a webpage that does not allow users to write comments), Web 2.0 displays UGC alongside the proprietor content. Examples of UGC include comments responding to a Facebook post, comments on product reviews (comments written in response to an online news article).
Aggregated User Representations Web 2.0 systems also allow users to leave evaluations of others’ content. These evaluations may relate to proprietor content, as well as UGC. Web 2.0 systems often encourage users to rate or vote on the content produced by others. Then, the system aggregates the ratings for others to view. The aggregated ratings take the form of some statistics or figures. Examples of these representations include the number of stars, total votes, usefulness votes, helpfulness ratios, among others. To delineate among the different types of user representations, there are deliberate and incidental aggregate user representations. Deliberate aggregate user representations include responses generated from directly requesting those responses from users. For instance, after displaying an opinion from a user, the Web 2.0 system may solicit readers to rate if that opinion was useful or not useful (e.g., 1 to 5 stars). An example of deliberate representation may include ratings of review helpfulness. Amazon.com displays the accumulated ratings of helpfulness in the form of a ratio (e.g., 40 out of 41 people found the review helpful). In contrast, incidental aggregate user representations include information captured by Web 2.0 systems. In particular, these representations do not reflect behaviors that users would like to express, but instead, they are computed by the Web 2.0 system and displayed with other information. Examples of these representations include the number of Facebook friends, number of views on a YouTube video, the timestamp of a particular comment or review, among others. These representations offer a unique persuasive quality in that online users have no control over them. As a result, they may serve to aid certain aspects of self-presentations from a warranting perspective.
Participatory Websites and Juxtaposition among Sources Participatory websites create unique theoretical challenges for CMC. Although the theoretical terms expressed previously aid in defining the various conceptual components involved in Web 2.0, they do not offer a set of theoretical
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propositions regarding the relationships among the concepts. From a communication perspective, the model elements of the sender, receiver, message, context, and feedback also offer little explanatory utility as these components mix to serve multiple roles in Web 2.0. For instance, a message proprietor may respond to UGC and create a conversation between a proprietor and a commenter. At the same time, other users contribute to this dynamic through rating both the proprietor content and/or the UGC. When the Web 2.0 system displays all these contents simultaneously, how do other readers process that information and continue in the participatory process by adding or rating the existing content? What if more than one commenter is involved? This question typifies the theoretical challenge in the study of CMC as new technology enable online communicators to interact at such a convergent level across multiple information sources and ratings.
Summary and Future Direction The current review began with an explanation of the communication perspective and elements in the communication model. With this perspective in mind, we reviewed a few of the theories involved in understanding CMC. The cues-filtered-out approaches assumed CMC’s lack of nonverbal cues limited communication. On the other hand, theories of interpersonal adaption and exploitation of media posit a more interactive process that may match and/or exceed face to face. Finally, the conceptual framework for understanding participatory websites provides a glimpse of the complexity and challenge of theory development. As research incrementally increases our understanding of CMC, technology is also on the forefront of altering the landscape of digital interaction. Web 2.0 site continue to modify both interface as well as the type of information available to users.
See also: Audiences, Media; Information Society; Social Media.
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