Speaker:

Lillian Lee, Charles Roy Davis Professor, Department of Computer Science and Department of Information Science, Cornell University

Title:

Online Discussion Dynamics: Early prediction of controversy; content removal as a moderation strategy

Abstract:

Part One: 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.

Part Two: Moderators of online communities often employ comment deletion as a tool. We ask here whether, beyond the positive effects of shielding a community from undesirable content, does comment removal actually cause the behavior of the comment’s author to improve? We examine this question in a particularly well-moderated community, the ChangeMyView subreddit. The standard analytic approach of interrupted time-series analysis unfortunately cannot answer this question of causality because it fails to distinguish the effect of having made a non-compliant comment from the effect of being subjected to moderator removal of that comment. We therefore leverage a “delayed feedback” approach based on the observation that some users may remain active between the time when they posted the non-compliant comment and the time when that comment is deleted. Applying this approach to such users, we reveal the causal role of comment deletion in reducing immediate noncompliance rates, although we do not find evidence of it having a causal role in inducing other behavior improvements. Our work thus empirically demonstrates both the promise and some potential limits of content removal as a positive moderation strategy, and points to future directions for identifying causal effects from observational data

Joint work with Cristian Danescu-Niculescu-Mizil, Jack Hessel, Kumar Bhargav Srinivasan, Chenhao Tan

Speaker Bio:

Lillian Lee is the Charles Roy Davies professor in the departments of computer science and of information science at Cornell University. Her research interests include natural language processing and computational social science. She is a AAAI Fellow, an ACL Fellow, and an ACM Fellow, and a former Sloan Fellow. She received one of three inaugural awards for the Test of Time (2002-2012) Paper on Computational Linguistics (joint with Bo Pang), and best paper awards at NAACL 2004 (joint with Regina Barzilay) and the IJCAI 2016 Natural Language Processing meets Journalism workshop (joint with Liye Fu and Cristian Danescu-Niculescu-Mizil). She earned a citation in "Top Picks: Technology Research Advances of 2004" by Technology Research News (also joint with Regina Barzilay). Her co-authored work has received several mentions in the popular press, including The New York Times, NPR's All Things Considered, and NBC's The Today Show.

Webinar:

Zoom link: https://northwestern.zoom.us/j/99055485716
Passcode: nico

About the Speaker Series:

Wednesdays@NICO is a vibrant weekly seminar series focusing broadly on the topics of complex systems and data science. It brings together attendees ranging from graduate students to senior faculty who span all of the schools across Northwestern, from applied math to sociology to biology and every discipline in-between. Please visit: https://bit.ly/WedatNICO for information on future speakers.

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