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 text mining, in particular, comment analysis. Further, I am involved in projects on patent classification and book recommendation.

Source code for my publications can be found here and on GitHub.

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.


Advised Master's Theses

  • Enriching Document Embeddings With Domain Knowledge
  • Modeling News Commenters for Discussion Recommendation
  • Jointly Learning Document and Label Embeddings for Hierarchically Labeled Text
  • Context-aware Classification of News Comments
  • Quality Management for Online News Comments 


Fine-Grained Classification of Offensive Language

Risch, Julian; Krebs, Eva; Löser, Alexander; Riese, Alexander; Krestel, Ralf in Proceedings of GermEval (co-located with KONVENS) Seite 38-44 . 2018 .

Social media platforms receive massive amounts of user-generated content that may include offensive text messages. In the context of the GermEval task 2018, we propose an approach for fine-grained classification of offensive language. Our approach comprises a Naive Bayes classifier, a neural network, and a rule-based approach that categorize tweets. In addition, we combine the approaches in an ensemble to overcome weaknesses of the single models. We cross-validate our approaches with regard to macro-average F1-score on the provided training dataset.
Weitere Informationen
Tagscomments_analysis  isg  myown  web_science