2022
DOI: 10.1007/s44204-022-00042-2
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People, posts, and platforms: reducing the spread of online toxicity by contextualizing content and setting norms

Abstract: We present a novel model of individual people, online posts, and media platforms to explain the online spread of epistemically toxic content such as fake news and suggest possible responses. We argue that a combination of technical features, such as the algorithmically curated feed structure, and social features, such as the absence of stable social-epistemic norms of posting and sharing in social media, is largely responsible for the unchecked spread of epistemically toxic content online. Sharing constitutes … Show more

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Cited by 7 publications
(2 citation statements)
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“…Nonetheless, this would not reflect poorly on the engineer, the construction 1 This is not to say that no attention has been given to these questions. Simon (2010), Rini (2017), Miller and Record (2017), and Record and Miller (2022) are examples.…”
Section: Environmental Epistemologymentioning
confidence: 99%
“…Nonetheless, this would not reflect poorly on the engineer, the construction 1 This is not to say that no attention has been given to these questions. Simon (2010), Rini (2017), Miller and Record (2017), and Record and Miller (2022) are examples.…”
Section: Environmental Epistemologymentioning
confidence: 99%
“…This means that crime information on locality based social media is not necessarily reflective of fact or provided by experts. Algorithmic surfacing can amplify particular issues at the cost of others, while the modularity of posts and comments can result in context collapse (Record & Miller, 2022). Given most individuals on social media are passive rather than active participants, the overall crime narrative displayed to the collective is largely driven by a small proportion of prolific posters who may or may not be well informed about crime.…”
Section: Social Media For Neighborhood Watchmentioning
confidence: 99%