Ash Catton


PhD Candidate, Clinical Psychology Student

Viral Conformity: Applying a Social Identity Perspective to Moral Outrage on Social Media


July 01, 2019

(Psychology)
Why does moral outrage go viral on social media? Expressions of moral outrage have become a common feature of modern life. Much of this can be attributed to the advent of Social Networking Sites (SNS) which have added new dimensions to the transmission of moral outrage by allowing it to go ‘viral’ as it is transmitted across vast audiences within a small amount of time (Crockett, 2017). Despite this, there does not appear to be any published research which has explored the potential role of social factors such as norm conformity in spreading moral outrage on SNS.

Moral outrage is a psychological state triggered by moral norm violations and includes cognitive, affective, and behavioural reactions (Tetlock, Kristel, Elson, Green, & Lerner, 2000). Specifically, moral outrage involves harsh character attributions towards transgressors, feelings of anger, and increased motivation to uphold moral norms (Tetlock, 2003). In functional terms, moral outrage is a tool which promotes prosocial behaviour by coordinating collective action such as punishing transgressors (Spring, Cameron, & Cikara, 2018). In this way, the anticipation of experiencing punishment for violating moral norms is a strong reason against transgression. However, the specific objects of moral norms are socially procured rather than innate mechanisms and are therefore not universally shared. For example, support for legalising euthanasia among New Zealander’s has been shown to vary depending on demographic differences such as religion, level of education, and whether one lives in an urban location (Young, Egan, Walker, Graham-DeMello, & Jackson, 2018).

In addition, SNS has changed the way that moral outrage is transmitted in several ways. Firstly, as moral norms are inferred by social environments, it would be expected that offline and first-hand encounters of norm violations be rarely experienced. This was shown by Hofmann, Wisneski, Brandt, and Skitka (2014) who found that immoral acts were more than twice as likely to be encountered via gossip than witnessed first-hand. SNS connects billions of people around the world thereby increasing the frequency of both gossip and exposure to transgressions. As SNS posts are usually public records, those posts which violate norms can be the subject of gossip which may then prompt an individual to seek out the offending post for direct evidence of the transgression. By contrast, direct evidence of offline transgressions is not usually preserved for widespread public scrutiny.

Secondly, SNS makes transgressions more salient given the ability to personalise social media feeds and choose to follow only those who express similar interests or values. For example, in a large scale study of 150 million tweets, it was found that political issues were usually discussed among those with similar ideologies (Barbera, Jost, Nagler, Tucker, & Bonneau, 2015). Indeed, it has been shown that an SNS user’s social network is a significant predictor of their political orientation (Colleoni, Rozza, & Arvidsson, 2014). Thus, if an individual hears about a norm violation on SNS it is likely to be from those in their social network, and already framed in a way consistent with that person’s ideological beliefs. This illustrates the role of social influence in the spread of outrage. For instance, it has been noted that several tweets sent by US President Donald Trump on some issues appeared to echo similar sentiment which had been expressed by Fox News minutes beforehand (Holmes, 2019).

Third, SNS makes it possible for moral outrage to go viral and reach a large audience in a short amount of time. For instance, emotionally-charged tweets tend to spread more quickly than emotionally-neutral messages (Stieglitz & Dang-Xuan, 2014) leading to what has been called “moral contagion” (Brady, Wills, Jost, Tucker, & Van Bavel, 2017). However, moral outrage on SNS is not limited to information sharing. As exposure to transgressions becomes viral, so too does the negative characterisation and subsequent shaming that accompanies it. In one example, a woman who posted a racially insensitive tweet before boarding a long-haul flight found that her tweet had gone viral before she landed, resulting in her twitter feed becoming what a journalist described as a “horror show” (Ronson, 2015). 

The capacity on SNS for these kinds of mass “pile-on’s” blurs the lines between moral shaming and cyberbullying. For example, Sawaoka and Monin (2018) found that judgments of expressions of viral outrage on SNS varied depending on whether the participant was a first-person contributor to the outraged discourse, or a third-person observer. Specifically, the third-person perspective was associated with greater feelings of sympathy towards the original transgressor. However, the literature on SNS and Computer Mediated Communication (CMC) suggests that these findings may reflect more than a mere change in perspective.

Research on deindividuation holds that it is possible for group norms to be temporarily adopted by an individual, thus making it possible for a single person to evaluate actions according to the norms adopted by whichever group they feel they belong to. The Social Identity model of Deindividuation (SIDE) posits that deindividuation results in a shift from a personal identity to the adoption of a group or social identity (Reicher, Spears, & Postmes, 1995). It follows from this that the evaluation of anti-normative actions similarly shifts. In addition, it has been recognised that visual anonymity, which is present by default on CMC, may induce deindividuation (Douglas & McGarty, 2002; Tom Postmes, Spears, & Lea, 2002; Tom Postmes, Spears, Sakhel, & de Groot, 2000).  Furthermore, as norms are socially produced, it has been recognised that group norms appear to be inductively inferred by observing patterns in communication online as cues (Lee & Lim, 2014; T. Postmes, Spears, & Lea, 2000).

References

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