News organizations enable online commenting with the goal of increasing user engagement and enhancing the quality of news and information. Unfortunately, online commenting platforms are often used as a place to vent anger, frustration, and express hatred, in general or towards specific groups. While there is a clear value in including reader comments, news organizations find themselves having to sift through and organize comments to ensure that commenters exchange views, opinions, and insights in a respectful and constructive manner, and to keep the discussion relevant to the issues discussed in the article. The goal of this project is to promote meaningful and constructive discussion online. Accordingly, we have developed computational methods to identify constructive comments.
For more information about this work, please see our papers.
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Kolhatkar. V. and M. Taboada (2017) Using New York Times Picks to identify constructive comments. Proceedings of the Workshop Natural Language Processing Meets Journalism, Conference on Empirical Methods in Natural Language Processing. Copenhagen. September 2017.
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Kolhatkar, V. and M. Taboada (2017) Constructive language in news comments. Proceedings of the 1st Abusive Language Online Workshop, 55th Annual Meeting of the Association for Computational Linguistics. Vancouver. August 2017, pp. 11-17.
Check out the web interface for this project.