Social Media as Information Sources Recency of updates and credibility of information
Abstract
Another important concept to examine for social media and credibility is cognitive elaboration. Cognitive elaboration is demonstrated in active participation in information processing (Defleur & Ball-Rokeach, 1989). This involvement process manifests in the mental process of attention, recognition and subsequent elaboration (Greenwald & Leavitt, 1984). A central tenet of involvement is the sense that the individual partakes in an active psychological processing of that content. Involvement can be gauged by observing several activities associated with the content. For example, talking about a webpage with others after reading it can be seen as evidence of involvement. As noted by Levy and Windhal (1984), thoughts and discussions after exposure can be seen as a positive type of audience involvement. Similar research has demonstrated that thinking about and sharing media content indicate increased involvement (Perloff, 1985). As noted by Rubin and Perse (1987), involvement “has been linked to media use motives that are grounded in the importance of the content and reflect a desire to acquire and share information” (p. 63). Moreover, opinion leaders appear to use media content for information acquisition and social utility (Lemish, 1985; Levy, 1978).
Social Media and Credibility JudgmentsThe MAIN Model and Recency of UpdatesThe MAIN model (Sundar, 2008) describes technological affordances that allow people to heuristically process cues when making judgments about the credibility of an online source. According to the model, system-generated pieces of information known as metrics are one type of affordance which can be used as a heuristic in making credibility judgments. One metric that may be especially heuristically appealing to people is an agency cue. Agency cues capitalize on heuristics that emphasize credibility cues that, for example, are computer- (rather than user-) generated.
One heuristic Sundar (2008) argues is often utilized is known as the machine heuristic, which is a shortcut through which people assign greater credibility to information that is verified or chosen by a machine or computer than by a person. People likely use this shortcut because a machine is seen as something that has no thoughts, emotions, or other biases, and therefore is perceived to be free from bias (whether or not the algorithm is actually free from bias.) This lack of perceived bias from a machine leads to a greater trust in the information provided by machines compared to the information provided by people such as editors, producers, and the like (Sundar & Nass, 2001). Similarly, this heuristic may also impact the way that consumers of online information process system-generated cues. These cues can even influence credibility judgments more strongly than the content of the message itself, depending on the degree to which such a heuristic is activated and how heuristically or peripherally a message is processed by a user. Past research exploring impression formation on Facebook has found that system-generated cues can be important determinants of social judgments about social media users (Kleck, Reese, Behnken, & Sundar, 2007; Tong, Van Der Heide, Langwell, & Walther, 2008; Utz, 2010), suggesting that system-generated cues can affect interpersonal judgments of a profile owner. - Radith Ann Jordan |