Studies have shown that people tend to match their behavior on social media platforms to the views and opinions of others as espoused by Jonas Colliander (2019). The authors conducted an empirical study that investigated the nature of Facebook consensus. In particular, they had sought to find out the influence exerted by conformity on people’s comments towards disinformation and their likelihood to share the same across Facebook (Colliander, 2019).
In that regard, the researchers investigated how people respond to a fake news article after being exposed to comments that are either favorable or critical to the article (Colliander, 2019). Outcomes from their study revealed that, after exposing participants to positive comments about a fake news article, they responded more positively and were more likely to share the article than after exposure to negative comments about the article. Similarly, Guo, Wen, & Yin (2019) also investigated social media consensus to determine how the nature of feedback collected from online reviews (whether positive or negative) influences conformity.
In contrast to Colliander’s (2019) approach, Guo, Wen, & Yin (2019) focused primarily on changes in people’s amplitude (negative and positive P300 amplitudes) towards online reviews depending on the general consensus in the reviews. In this case, participants in the study had been asked to evaluate and rate online reviews in order to establish whether they would show more or less conformity (Guo, Wen, & Yin, 2019). Outcomes from the study revealed that participants were more likely to perceive online reviews that were incongruent to their general opinions as negative feedback and those that were congruent as positive feedback.
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Just like the revelations presented by Colliander (2019), Guo, Wen, & Yin (2019) found that the participant’s opinions matched those of the majority social media users, and in this case online reviewers. However, unlike Colliander (2019), Guo, Wen, & Yin (2019) provide further insights regarding how people filter out the majority opinion across social media contexts. Here, the researchers reveal the brain’s capacity to automatically categorize social cues with respect to the opinions of the majority opinion (Guo, Wen, & Yin (2019). Accordingly, this capability shapes an individual’s conformity, hence amplitude towards individual online reviews.
Perfumi, Bagnoli, Caudek, & Guazzini (2019) and Mallinson & Hatemi (2018) have also conducted studies to examine the influence of conformity on people’s opinion change. Unlike Colliander (2019) and Guo, Wen, & Yin (2019) who based their studies on Facebook opinions and online reviews respectively, Perfumi et al. (2018) focused on social contexts within computer-mediated-communication. Likewise, Mallinson & Hatemi (2018) took a different approach by basing their study on generalized social contexts.
In particular, the authors investigated the role of conformity in shaping people’s political opinions and political values (Mallinson & Hatemi, 2018). While both research teams fail to make relevance to the concept of Facebook consensus, they provide background information concerning the role of conformity in shaping people’s opinions from different points of view. For example, Perfumi et al. (2019) contend that people are likely to conform with informational influence than they are with normative influence within computer-based contexts. In addition, the impact of both types of influence becomes less salient when individuals undergo deindividuation (Perfumi et al., 2019).
Likewise, Mallinson & Hatemi (2018) have shown that conformity with social pressures and information is likely to change people’s political opinions. In that regard, the authors contend that information that is provided alongside social pressure is more effective in changing political opinion than information alone. His means that social pressure generates greater conformity than information with respect to change in people’s political values.
