2021
DOI: 10.1177/0894439320985527
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Social Norms and the Dynamics of Online Incivility

Abstract: Online discussions are performed in the gaze of fellow users. To increase engagement, platforms typically let these users evaluate the comments made by others through rating systems (e.g., via Likes or Down/Up votes). Understanding how such ratings shape, and are shaped by, features of the underlying discussion is important for our understanding of online behavior. In this study, we focus on an increasingly concerning aspect of online discussions: incivility. We draw on the theory of normative social behavior … Show more

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Cited by 41 publications
(37 citation statements)
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“…In fact, the findings also show that politicians can somewhat control users' use of incivility through leading by example. Consistent with prior studies (Gervais, 2017;Kim et al, 2021;Rega and Marchetti, 2021;Shmargad et al, 2021), our estimations provide evidence that using incivil language in the original post increases the probability of said post receiving incivil comments. Effects resulting from personal characteristics of the posting politicians are overall weaker and opposite to the direction we expected based on previous research.…”
Section: Discussionsupporting
confidence: 88%
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“…In fact, the findings also show that politicians can somewhat control users' use of incivility through leading by example. Consistent with prior studies (Gervais, 2017;Kim et al, 2021;Rega and Marchetti, 2021;Shmargad et al, 2021), our estimations provide evidence that using incivil language in the original post increases the probability of said post receiving incivil comments. Effects resulting from personal characteristics of the posting politicians are overall weaker and opposite to the direction we expected based on previous research.…”
Section: Discussionsupporting
confidence: 88%
“…Indeed, previous studies have found "significant spikes of abuse on particular days" (Ward and McLoughlin, 2020, p. 61; see also Su et al, 2018 for social media pages of news outlets), but also that incivility always seems to be prevalent on social media to a certain degree (Theocharis et al, 2020). As indicated above, research has also shown that incivility in the original post influences the amount of incivility in user comments (Gervais, 2017;Kim et al, 2021;Rega and Marchetti, 2021;Shmargad et al, 2021). This kind of "contagious incivility" has been associated with different mechanisms, with explanations ranging from behavioral mimicry to incivility increasing feelings of anger or changing social media users' perceived social norms (for an overview, see Kim et al, 2021).…”
Section: Post Characteristicsmentioning
confidence: 86%
“…The initial utopian vision of the Internet as a place for equal participation, inclusive political dialogue, a new public sphere, and exposure to diverse opinions has been counterbalanced by concerns about disinhibition, privacy, surveillance, intimidation, fake news, hate speech, trolling, incivility, and speech regulation (Hiltz & Turoff, 1978;Katz & Rice, 2002;Mihaylov et al, 2018;Shmargad et al, 2021). Dutton (1996) concluded that some of those visions become tenuous without appropriate "rules of order" and norms.…”
Section: Discussionmentioning
confidence: 99%
“…Compliance with that group identity and associated behaviors must be visible in some way, for others to acknowledge, accept, and reinforce that compliance (Lapinski & Rimal, 2005). Shmargad et al (2021) made Lapinski and Rimal's (2005) distinction between individuals' perceived or subjective norms and collective norms (a social systems' expectations about attitudes and behaviors, which emerge and are constructed through social interaction within a salient group), more explicit, arguing that both descriptive and injunctive norms occur at both individual and collective levels. Similarly, Sewell described how surveillance may be "horizontal" through group members (reflecting CC) but also "vertical" through organizational information and communication systems (reflecting bureaucratic control).…”
Section: Group Identification Offlinementioning
confidence: 99%
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