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Psychological biases for cheater detection shape social transmission of political news stories and trust
Abstract: People receive a central part of their political news via interpersonal communication. The persistent circulation on social media of stories about for example Donald Trump’s tax avoidance or the “Bill Gates’ microchip” conspiracy theory about the Corona vaccine illustrate how political information spreads and endures in social networks. Yet not all types of political news stories are equally likely to “go viral” in interpersonal communication. Why are some stories transmitted massively in interpersonal communication and have strong impact on political opinions while others die out almost immediately? In this talk, I integrate cognitive and evolutionary psychology into the political science literature on the two-step communication flow to address this question. I argue that political news stories that resonate with deep-seated psychological biases for cheater detection will be transmitted more and have stronger impact on opinions in interpersonal communication. I present experimental evidence collected in the United States supporting this argument. The experiments employ the Chain Transmission Design which specifically detects psychological biases by tracking how information deteriorates in social transmission. The findings advance understanding of biases in social information circulation and the sources of political distrust: These democratic challenges are not merely driven by strategic elites but also by evolved “psychological news criteria” of the human mind.
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