Analysis of 25,000 users reveals how negativity biases influence news selection, suggesting implications for digital information reliability.
A considerable body of work finds evidence of negativity biases in news production and consumption. These biases have consequences for the reliability and accuracy of digital information. For this special issue, focused on the “complex interplay of technology and human biases,” we consider how individual-level variation in negativity biases impacts both news selection and news provision. Using digital trace data, we analyze the news selections of roughly 25,000 SmartNews users over 6 months. We find evidence of trait-level differences in individuals’ negativity biases in news selection and consider the degree to which those trait-level differences in negativity biases are sustained through algorithmically personalized news feeds.
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Noh et al. (2025) studied this question.
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