Hasso-Plattner-Institut
Prof. Dr. Felix Naumann
  
 

Julian Risch

I am a Ph.D. student at the Information Systems Group and a member of the HPI Research School. My research focuses on topic modeling and deep learning with applications in the field of comment analysis. Further, I am involved in projects on patent classification and book recommendation.

Contact Information

Prof.-Dr.-Helmert-Straße 2-3
D-14482 Potsdam
Room: F-2.08

Phone: +49 331 5509 272

Email: Julian Risch

Open Master's Theses

I provide supervision for Master's theses in the area of News Comment Analysis, e.g., Toxic Comment Classification, User Engagement Prediction, Comment Recommendation, and Discussion Summarization/Visualization. Feel free to schedule an informal meeting with me to discuss details of these topics and/or your own ideas.

Teaching

Publications

Prediction for the Newsroom: Which Articles Will Get the Most Comments?

Ambroselli, Carl; Risch, Julian; Krestel, Ralf; Loos, Andreas in Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL) page 193-199 . ACL , 2018 .

The overwhelming success of the Web and mobile technologies has enabled millions to share their opinions publicly at any time. But the same success also endangers this freedom of speech due to closing down of participatory sites misused by individuals or interest groups. We propose to support manual moderation by proactively drawing the attention of our moderators to article discussions that most likely need their intervention. To this end, we predict which articles will receive a high number of comments. In contrast to existing work, we enrich the article with metadata, extract semantic and linguistic features, and exploit annotated data from a foreign language corpus. Our logistic regression model improves F1-scores by over 80% in comparison to state-of-the-art approaches.
Prediction for the Newsro... - Download
Further Information
Tags comments_analysis  hpi  isg  web_science