Prof. Dr. Felix Naumann

Project Description

The comment sections of online newspapers are an important space to indulge in political discussions and discuss various opinions. These discussion forums have to be moderated due to the misuse by spammers, haters, trolls, and means of propaganda. This moderation process is very expensive and many online news providers have discontinued their comment sections. With more and more political campaigning, or even agitation being distributed over the internet, serious and safe platforms to discuss political topics are increasingly important.

In this project, we therefore analyze comments, users, and articles to understand the dynamics, the information flow, and the interactions in the comment sections. We work on detecting inappropriate comments, predicting popular news topics, identifying fake news and recommending information.


  • Hate Speech Detection
  • Volume Prediction

Associated Activities

  • Master Project, 2017: Hate Speech Detection
  • Master Thesis by Dustin Gläser, 2017: Detection of Inappropriate Content in Online Comments
  • Master Thesis by Christian Godde, 2016: Classification of German Newspaper Comments

Project-Related Publications

  • Ambroselli, C., Risch, J., Krestel, R., Loos, A.: Prediction for the Newsroom: Which Articles Will Get the Most Comments? 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2018). ACL, New Orleans, Louisiana, USA (2018).
  • Godde, C., Lazaridou, K., Krestel, R.: Classification of German Newspaper Comments. Proceedings of the Conference Lernen, Wissen, Daten, Analysen. pp. 299-310. CEUR-WS.org (2016).