Understanding the Sorting Algorithm: Emotion Contagion and Comment Ranking on a Politically Polarizing News Article
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Abstract
Online news platforms tend to sort and rank comments in different ways, other than chronologically displaying them. Previous research has found that bias in ranking algorithms can promote political bias and contribute to ideological polarization. We compared chronologically sequenced versus algorithmically ranked comments on a controversial Foxnews.com article using Linguistic Inquiry and Word Count software and content analysis. Findings reveal that the ranking algorithm promotes comments with a positive emotional tone and discourages negative comments, suggesting that the algorithm is partially neutralizing the ideological bias of the Foxnews.com platform. Ranking was also affected by comment length and upvotes and downvotes.
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