How social learning amplifies moral outrage expression
in online social networks

How social learning amplifies moral outrage expression in online social networks

Author

Brady, McLoughlin, Doan and Crockett

Year
2021
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How social learning amplifies moral outrage expression in online social networks

William J. Brady, Killian McLoughlin, Tuan N. Doan, Molly J. Crockett. 2021 (View Paper →)

Moral outrage shapes fundamental aspects of social life and is now widespread in online social networks. Here, we show how social learning processes amplify online moral outrage expressions over time.

In two preregistered observational studies on Twitter (7331 users and 12.7 million total tweets) and two preregistered behavioural experiments (N = 240), we find that positive social feedback for outrage expressions increases the likelihood of future outrage expressions, consistent with principles of reinforcement learning.

In addition, users conform their outrage expressions to the expressive norms of their social networks, suggesting norm learning also guides online outrage expressions. Norm learning overshadows reinforcement learning when normative information is readily observable: in ideologically extreme networks, where outrage expression is more common, users are less sensitive to social feedback when deciding whether to express outrage.

Our findings highlight how platform design interacts with human learning mechanisms to affect moral discourse in digital public spaces.

The relevant parts of the abstract can be copied here in italics...

The mechanics of social media amplify moral outrage as people seek validation from others for their stance? This is a good example of a reinforcing feedback loop in a complex system.