2022
DOI: 10.1609/icwsm.v16i1.19289
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Effect of Popularity Shocks on User Behaviour

Abstract: Users often post on content-sharing platforms in the hope of attracting high engagement from viewers. Some posts receive unusual attention and go "viral", eliciting a significant response (likes, views, shares) to the creator in the form of popularity shocks. Past theories have suggested a sense of reputation as one of the key drivers of online activity and the tendency of users to repeat fruitful behaviors. Based on these, we theorize popularity shocks to be linked with changes in the behavior of users. In th… Show more

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Cited by 8 publications
(6 citation statements)
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“…For example, a reinforcement-learning account of motivation (24) predicts that a higher rate of rewards (e.g., more likes per post, on average) should make posting more valuable (i.e., more worth the effort required to post and also worth giving up other rewards in place of posting), leading users to post more frequently in the near future. This prediction has been supported in several social media datasets (25,26), including through computational modeling (27). Moreover, receiving more rewards for posts of a certain type should lead users to post similar posts in the future, as demonstrated in recent studies (26,28).…”
Section: Introductionmentioning
confidence: 66%
“…For example, a reinforcement-learning account of motivation (24) predicts that a higher rate of rewards (e.g., more likes per post, on average) should make posting more valuable (i.e., more worth the effort required to post and also worth giving up other rewards in place of posting), leading users to post more frequently in the near future. This prediction has been supported in several social media datasets (25,26), including through computational modeling (27). Moreover, receiving more rewards for posts of a certain type should lead users to post similar posts in the future, as demonstrated in recent studies (26,28).…”
Section: Introductionmentioning
confidence: 66%
“…On the other hand, employees who are, on average, likely to email many colleagues outside their immediate clique are less likely to receive replies. These insights can generalize to understanding communication behavior on other small-world networks, such as social media platforms, where research on the virality of content [75,76], hot streaks in user popularity [77], and their consequences for user and community behavior [78,79] all discuss the importance of social network features in understanding and modeling communication cascades.…”
Section: Discussionmentioning
confidence: 87%
“…Empirical studies have also predicted what content goes viral on platforms like X, formerly Twitter, and YouTube (Figueiredo, Benevenuto, and Almeida 2011;Weng, Menczer, and Ahn 2013). Recent research has also examined the consequences of popularity shocks on online users (Gurjar et al 2022).…”
Section: Related Work Popular Content and Algorithmic Curationmentioning
confidence: 99%
“…Algorithms that cause popularity spikes are often opaque about how they operate (Eslami et al 2015), and thus create unexpected moments of popularity or virality. Prior work on virality focuses on the content that became viral (Berger and Milkman 2012) or the users who create content (Gurjar et al 2022).…”
Section: Introductionmentioning
confidence: 99%