For bachelor students we offer German lectures on database systems in addition with paper- or project-oriented seminars. Within a one-year bachelor project students finalize their studies in cooperation with external partners. For master students we offer courses on information integration, data profiling, search engines and information retrieval enhanced by specialized seminars, master projects and advised master theses.
The Web Science group focuses on various topics related to the Web, such as Information Retrieval, Natural Language Processing, Data Mining, Knowledge Discovery, Social Network Analysis, Entity Linking, and Recommender Systems. The group is particularly interested in Text Mining to deal with the vast amount of unstructured and semi-structured information available on the Web.
Most of our research is conducted in the context of larger research projects, in collaboration across students, across groups, and across universities. We strive to make available most of our data sets and source code.
Toxic Comment Classification We participated in the Toxic Comment Classification Challenge (Link), which was a Kaggle challenge with the goal to identify and classify toxic online comments. In collaboration with our colleagues from the DATEXIS group at Beuth Hochschule für Technik Berlin, we finished in the top 2% of the leaderboard and achieved 54th place out 4551 teams.
Aggression Identification We participated in the First Shared Task on Aggression Identification (Link), which is part of the First Workshop on Trolling, Aggression and Cyberbullying at the 27th International Conference of Computational Linguistics (COLING 2018). Our team achieved 2nd place out of 30 teams at the task of classifying social media posts as ‘Overtly Aggressive’, ‘Covertly Aggressive’, or ‘Non-aggressive’ on an unseen test dataset. We will submit a description of our approach to COLING 2018 and publish the augmented dataset here under Creative Commons Non-Commercial Share-Alike 4.0 licence CC-BY-NC-SA 4.0.