Using Argument Mining to Assess the Argumentation Quality of Essays - Wachsmuth, Henning; Al Khatib, Khalid; Stein, Benno (Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers)

UTCNN: a Deep Learning Model of Stance Classification on Social Media Text - Chen, Wei-Fan; Ku, Lun-Wei (Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics)

Visual Analysis of Argumentation in Essays - Kiesel, Dora; Riehmann, Patrick; Wachsmuth, Henning; Stein, Benno; Fröhlich, Bernd (IEEE Transactions of Visualization & Computer Graphics)

Visualization of the Topic Space of Argument Search Results in args. me - Ajjour, Yamen; Wachsmuth, Henning; Kiesel, Dora; Riehmann, Patrick; Fan, Fan; Castiglia, Giuliano; Adejoh, Rosemary; Fröhlich, Bernd; Stein, Benno (Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations)

WAT-SL: A Customizable Web Annotation Tool for Segment Labeling - Kiesel, Johannes; Wachsmuth, Henning; Al Khatib, Khalid; Stein, Benno (Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics)

We Like, We Post: A Joint User-Post Approach for Facebook Post Stance Labeling - Chen, Wei-Fan; Ku, Lun-Wei (IEEE Transactions on Knowledge and Data Engineering)

Webis at the CLEF 2017 Dynamic Search Lab - Hagen, Matthias; Kiesel, Johannes; Alshomary, Milad; Stein, Benno (Working Notes of CLEF 2017 - Conference and Labs of the Evaluation Forum)

What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing - Nouri, Zahra; Gadiraju, Ujwal; Engels, Gregor; Wachsmuth, Henning (Proceedings of the 32nd ACM Conference on Hypertext and Social Media)

Wikipedia Text Reuse: Within and Without - Alshomary, Milad; Völske, Michael; Licht, Tristan; Wachsmuth, Henning; Stein, Benno; Hagen, Matthias; Potthast, Martin (Advances in Information Retrieval)
We study text reuse related to Wikipedia at scale by compiling the first corpus of text reuse cases within Wikipedia as well as without (i.e., reuse of Wikipedia text in a sample of the Common Crawl). To discover reuse beyond verbatim copy and paste, we employ state-of-the-art text reuse detection technology, scaling it for the first time to process the entire Wikipedia as part of a distributed retrieval pipeline. We further report on a pilot analysis of the 100 million reuse cases inside, and the 1.6 million reuse cases outside Wikipedia that we discovered. Text reuse inside Wikipedia gives rise to new tasks such as article template induction, fixing quality flaws, or complementing Wikipedia's ontology. Text reuse outside Wikipedia yields a tangible metric for the emerging field of quantifying Wikipedia's influence on the web. To foster future research into these tasks, and for reproducibility's sake, the Wikipedia text reuse corpus and the retrieval pipeline are made freely available.

WordForce: Visualizing Controversial Words in Debates - Chen, Wei-Fan; Lin, Fang-Yu; Ku, Lun-Wei (Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations)