Spatial Games of Fake News
Matthew I Jones, Scott D. Pauls, Feng Fu

TL;DR
This paper models the spread of fake news on social networks, showing how network structure influences misinformation resilience and demonstrating that targeted fact-checking can significantly reduce fake news dissemination.
Contribution
It introduces a game-theoretic model of peer policing for fake news, analyzes network effects on misinformation spread, and evaluates targeted fact-checking strategies using real social network data.
Findings
Network structure enables fake news to form echo chambers, increasing resistance to fact-checking.
Targeted fact-checking can be highly effective with fewer resources.
Analytical conditions for effective crowdsourced fact-checking are derived.
Abstract
To curb the spread of fake news on social media platforms, recent studies have considered an online crowdsourcing fact-checking approach as one possible intervention method to reduce misinformation. However, it remains unclear under what conditions crowdsourcing fact-checking efforts deter the spread of misinformation. To address this issue, we model such distributed fact-checking as `peer policing' that will reduce the perceived payoff to share or disseminate false information (fake news) and also reward the spread of trustworthy information (real news). By simulating our model on synthetic square lattices and small-world networks, we show that the presence of social network structure enables fake news spreaders to be self-organized into echo chambers, thereby providing a boost to the efficacy of fake news and thus its resistance to fact-checking efforts. Additionally, to study our…
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Taxonomy
TopicsMisinformation and Its Impacts · Spam and Phishing Detection · Mobile Crowdsensing and Crowdsourcing
