Something's Brewing! Early Prediction of Controversy-causing Posts from Discussion Features

April 15, 2019 ยท Declared Dead ยท ๐Ÿ› North American Chapter of the Association for Computational Linguistics

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Authors Jack Hessel, Lillian Lee arXiv ID 1904.07372 Category cs.CL: Computation & Language Cross-listed cs.SI, physics.soc-ph Citations 77 Venue North American Chapter of the Association for Computational Linguistics Last Checked 3 months ago
Abstract
Controversial posts are those that split the preferences of a community, receiving both significant positive and significant negative feedback. Our inclusion of the word "community" here is deliberate: what is controversial to some audiences may not be so to others. Using data from several different communities on reddit.com, we predict the ultimate controversiality of posts, leveraging features drawn from both the textual content and the tree structure of the early comments that initiate the discussion. We find that even when only a handful of comments are available, e.g., the first 5 comments made within 15 minutes of the original post, discussion features often add predictive capacity to strong content-and-rate only baselines. Additional experiments on domain transfer suggest that conversation-structure features often generalize to other communities better than conversation-content features do.
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