SOURCE-LINKED INTELLIGENCE

Echo Chambers: Online Segregation, Mechanisms, and Consequences

CORDIS · observation · Publication date unknown

chambers. The project consists of three parts. First, I will create a new dataset of the slant (political leaning) of millions of articles using high-resolution data, expert ratings, and advances in large language models. I will use this dataset to provide the first estimate of online segregation based on the slant of articles. Second, instead of fixing the set of articles and analyzing consumer behavior, I will fix the audience and analyze how outlets tailor articles to their consumers, and whether this increases segregation. I will complement the descriptive estimates of how outlets distribute news with a casual analysis of whether the internet and social media affect the news that outlets produce. Third, I will elicit individuals willingness to pay for various articles and causally estimate how the articles people typically avoid affect their attitudes when they are consumed. I will use these estimates to decompose the relative importance of two theories for how news polarizes attitudes: differences in preference for like-minded news and heterogeneity in the effects of news. ec

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recordType

award

status

SIGNED

region

EU

value

1491250

unit

EUR