This page lists all computational argumentation publications co-authored by members of the Webis group. Other publications of Webis are found here.
2024
ACL 2024. LLM-based Mitigation of Inappropriate Argumentation using Reinforcement Learning from Machine Feedback.
Timon Ziegenbein, Gabriella Skitalinskaya, Alireza Bayat Makou, and Henning Wachsmuth. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics, to appear, 2024.
NAACL 2024. A School Student Essay Corpus for Analyzing Interactions of Argumentative Structure and Quality.
Maja Stahl, Nadine Michel, Sebastian Kilsbach, Julian Schmidtke, Sara Rezat, and Henning Wachsmuth. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics, pages 2661–2674, 2024. [paper] [bib]
LREC-COLING 2024b. Argument Quality Assessment in the Age of Instruction-Following Large Language Models. Henning Wachsmuth, Gabriella Lapesa, Elena Cabrio, Anne Lauscher, Joonsuk Park, Eva Maria Vecchi, Serena Villata and Timon Ziegenbein. The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, pages 1519–1538, 2024. [paper] [bib]
LREC-COLING 2024a. Identifying the Human Values behind Arguments in Diverse Sources.
Nailia Mirzakhmedova, Johannes Kiesel, Milad Alshomary, Maximilian Heinrich, Nicolas Handke, Xiaoni Cai, Valentin Barriere, Doratossadat Dastgheib, Omid Ghahroodi, MohammadAli SadraeiJavaheri, Ehsaneddin Asgari, Lea Kawaletz, Henning Wachsmuth and Benno Stein. The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, pages 16121–16134, 2024. [paper] [bib]
2023
Findings of EMNLP 2023. Mind the Gap: Automated Corpus Creation for Enthymeme Detection and Reconstruction in Learner Arguments.
Maja Stahl, Nick Düsterhus, Mei-Hu Chen, and Henning Wachsmuth. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 4703–4717, 2023. [paper] [bib]
INLG 2023. Claim Optimization in Computational Argumentation.
Gabriella Skitalinskaya, Maximilian Spliethöver, and Henning Wachsmuth. In Proceedings of the 16th International Natural Language Generation Conference, pages 134–152, 2023. [paper] [bib]
SIGDIAL 2023b. Frame-oriented Summarization of Argumentative Discussions.
Shahbaz Syed, Timon Ziegenbein, Philipp Heinisch, Henning Wachsmuth, and Martin Potthast. In Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue, pages 114–129, 2023. [paper] [bib]
SIGDIAL 2023a. A New Dataset for Causality Identification in Argumentative Texts.
Khalid Al Khatib, Michael Völske, Anh Le, Shahbaz Syed, Martin Potthast, and Benno Stein. In Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue, pages 349–354, 2023. [paper] [bib]
ACL 2023b. To Revise or Not to Revise: Learning to Detect Improvable Claims for Argumentative Writing Support.
Gabriella Skitalinskaya and Henning Wachsmuth. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, pages 15799–15816, 2023. [paper] [bib]
ACL 2023a. Modeling Appropriate Language in Argumentation.
Timon Ziegenbein, Shahbaz Syed, Felix Lange, Martin Potthast, and Henning Wachsmuth. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, pages 4344–4363, 2023. [paper] [bib]
EACL 2023b. Mining, Assessing, and Improving Arguments in NLP and the Social Sciences.
Gabriella Lapesa, Eva Maria Vecchi, Serena Villata, and Henning Wachsmuth. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Tutorial Abstracts, pages 1–6, 2023. [paper] [bib]
EACL 2023a. Conclusion-based Counter-Argument Generation.
Milad Alshomary and Henning Wachsmuth. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, pages 957–967, 2023. [paper] [bib]
Findings of EACL 2023. Topic Ontologies for Arguments.
Yamen Ajjour, Johannes Kiesel, Benno Stein and Martin Potthast. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, pages 1411–1427, 2023. [paper] [bib]
2022
TACL 2022. On the Role of Knowledge in Computational Argumentation.
Anne Lauscher, Henning Wachsmuth, Iryna Gurevych, and Goran Glavaš. Transactions of the Association for Computational Linguistics 10:1392–1422, 2022. [paper] [bib]
ArgMining 2022. Analyzing Culture-Specific Argument Structures in Learner Essays.
Wei-Fan Chen, Mei-Hua Chen, Garima Mudgal, and Henning Wachsmuth. In Proceedings of the 9th Workshop on Argument Mining, pages 51–61, 2022. [paper] [bib]
COMMA 2022. Generating Contrastive Snippets for Argument Search.
Milad Alshomary, Jonas Rieskamp, and Henning Wachsmuth. In Proceedings of the 9th International Conference on Computational Models of Argument, pages 21–32, 2022. [paper]
ACL 2022b. The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments.
Milad Alshomary, Roxanne El Baff, Timon Gurcke, and Henning Wachsmuth. In Proceedings of the Joint Conference of the 60th Annual Meeting of the Association for Computational Linguistics, pages 8782–8797, 2022. [paper] [bib]
ACL 2022a. Identifying the Human Values behind Arguments.
Johannes Kiesel, Milad Alshomary, Nicolas Handke, Xiaoni Cai, Henning Wachsmuth, and Benno Stein. In Proceedings of the Joint Conference of the 60th Annual Meeting of the Association for Computational Linguistics, pages 4459–4471, 2022. [paper] [bib]
ECIR 2022. Overview of Touché 2022: Argument Retrieval.
Alexander Bondarenko, Maik Fröbe, Johannes Kiesel, Shahbaz Syed, Timon Gurcke, Meriem Beloucif, Alexander Panchenko, Chris Biemann, Benno Stein, Henning Wachsmuth, Martin Potthast, and Matthias Hagen. In Proceedings of the 44th European Conference on Information Retrieval, pages 339–346, 2022. [paper]
2021
ArgMining 2021c. Image Retrieval for Arguments Using Stance-Aware Query Expansion.
Johannes Kiesel, Nico Reichenbach, Benno Stein, and Martin Potthast. In Proceedings of the 8th Workshop on Argument Mining, pages 36–45, 2021. [paper] [bib]
ArgMining 2021b. Assessing the Sufficiency of Arguments through Conclusion Generation.
Timon Gurcke, Milad Alshomary, and Henning Wachsmuth. In Proceedings of the 8th Workshop on Argument Mining, pages 67–77, 2021. [paper] [bib]
ArgMining 2021a. Key Point Analysis via Contrastive Learning and Extractive Argument Summarization.
Milad Alshomary, Timon Gurcke, Shahbaz Syed, Philipp Heinisch, Maximilian Spliethöver, Philipp Cimiano, Martin Potthast, and Henning Wachsmuth. In Proceedings of the 8th Workshop on Argument Mining, pages 184–189, 2021. [paper] [bib]
CUI 2021. The Meant, the Said, and the Understood: Conversational Argument Search and Cognitive Biases.
Johannes Kiesel, Damiano Spina, Henning Wachsmuth, and Benno Stein. In Proceedings of the 3rd Conference on Conversational User Interfaces, 2021. [paper] [bib]
ACL-IJCNLP 2021b. Syntopical Graphs for Computational Argumentation Tasks.
Joe Barrow, Rajiv Jain, Nedim Lipka, Franck Dernoncourt, Vlad Morariu, Varun Manjunatha, Douglas Oard, Philip Resnik, and Henning Wachsmuth. In Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, pages 1583–1595, 2021. [paper] [bib]
ACL-IJCNLP 2021a. Employing Argumentation Knowledge Graphs for Neural Argument Generation.
Khalid Al Khatib, Lukas Trautner, Henning Wachsmuth, Yufang Hou, and Benno Stein. In Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, pages 4744–4754, 2021. [paper] [bib]
Findings of ACL 2021b. Counter-Argument Generation by Attacking Weak Premises.
Milad Alshomary, Shahbaz Syed, Arkajit Dhar, Martin Potthast, and Henning Wachsmuth. In Findings of the Association for Computational Linguistics: ACL 2021, pages 1816–1827, 2021. [paper] [bib]
Findings of ACL 2021a. Generating Informative Conclusions for Argumentative Texts.
Shahbaz Syed, Khalid Al Khatib, Milad Alshomary, Henning Wachsmuth, and Martin Potthast. In Findings of the Association for Computational Linguistics: ACL 2021, pages 3482–3493, 2021. [paper] [bib]
EACL 2021b. Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale.
Gabriella Skitalinskaya, Jonas Klaff, and Henning Wachsmuth. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics, pages 1718–1729, 2021. [paper] [bib]
EACL 2021a. Belief-based Generation of Argumentative Claims.
Milad Alshomary, Wei-Fan Chen, Timon Gurcke, and Henning Wachsmuth. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics, pages 224–233, 2021. [paper] [bib]
ECIR 2021. Overview of Touché 2021: Argument Retrieval.
Alexander Bondarenko, Lukas Gienapp, Maik Fröbe, Meriem Beloucif, Yamen Ajjour, Alexander Panchenko, Chris Biemann, Benno Stein, Henning Wachsmuth, Martin Potthast, and Matthias Hagen. In Proceedings of the 43rd European Conference on Information Retrieval, pages 574–582, 2021. [paper]
TVCG/VIS 2021. Visual Analysis of Argumentation in Essays.
Dora Kiesel, Patrick Riehmann, Henning Wachsmuth, Benno Stein, and Bernd Fröhlich. IEEE Transactions of Visualization & Computer Graphics 27(2), pages 1139–1148, 2021. [paper]
2020
ArgMining 2020c. Argument from Old Man’s View: Assessing Social Bias in Argumentation.
Maximilian Spliethöver and Henning Wachsmuth. In Proceedings of the 7th Workshop on Argument Mining, pages 76–87, 2020. Best Paper Award [paper] [bib]
ArgMining 2020b. Semi-Supervised Cleansing of Web Argument Corpora.
Jonas Dorsch and Henning Wachsmuth. In Proceedings of the 7th Workshop on Argument Mining, pages 19–29, 2020. [paper] [bib]
ArgMining 2020a. Style Analysis of Argumentative Texts by Mining Rhetorical Devices.
Khalid Al-Khatib, Viorel Morari, and Benno Stein. In Proceedings of the 7th Workshop on Argument Mining, pages 106–116, 2020. [pages] [bib]
PEOPLES 2020. Persuasiveness of News Editorials depending on Ideology and Personality.
Roxanne El Baff, Khalid Al-Khatib, Benno Stein, and Henning Wachsmuth. In Proceedings of the Third Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media, pages 29–40, 2020. [pages] [bib]
COLING 2020b. Intrinsic Quality Assessment of Arguments.
Henning Wachsmuth and Till Werner. In Proceedings of the 28th International Conference on Computational Linguistics, pages 6739–6745, 2020. [pages] [bib]
COLING 2020a. News Editorials: Towards Summarizing Long Argumentative Texts.
Shahbaz Syed, Roxanne El Baff, Johannes Kiesel, Khalid Al-Khatib, Benno Stein, and Martin Potthast. In Proceedings of the 28th International Conference on Computational Linguistics, pages 5384–5396, 2020. [pages] [bib]
NLP+CSS 2020. Analyzing Political Bias and Unfairness in News Articles at Different Levels of Granularity.
Wei-Fan Chen, Khalid Al-Khatib, Henning Wachsmuth, and Benno Stein. In Proceedings of the Fourth Edition of the Natural Language Processing and Computational Social Science Workshop, pages 149–154, 2020. [paper] [bib]
EMNLP 2020. Detecting Media Bias in News Articles using Gaussian Bias Distributions.
Wei-Fan Chen, Khalid Al-Khatib, Benno Stein, and Henning Wachsmuth. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 4290–4300, 2020. [paper] [bib]
CEUR 2020. Overview of Touché 2020: Argument Retrieval.
Alexander Bondarenko, Maik Fröbe, Meriem Beloucif, Lukas Gienapp, Yamen Ajjour, Alexander Panchenko, Chris Biemann, Benno Stein, Henning Wachsmuth, Martin Potthast, and Matthias Hagen. Working Notes Papers of the CLEF 2020 Evaluation Labs, volume 2696 of CEUR Workshop Proceedings, 2020. [paper]
SIGIR 2020. Extractive Snippet Generation for Arguments.
Milad Alshomary, Nick Düsterhus, and Henning Wachsmuth. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 1969–1972, 2020. [paper]
ACL 2020d. Target Inference in Argument Conclusion Generation.
Milad Alshomary, Shahbaz Syed, Martin Potthast, and Henning Wachsmuth. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 4334–4345, 2020. [paper][bib]
ACL 2020c. Analyzing the Persuasive Effect of Style in News Editorial Argumentation.
Roxanne El Baff, Henning Wachsmuth, Khalid Al Khatib, and Benno Stein. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 3154–3160, 2020. [paper][bib]
ACL 2020b. Exploiting Personal Characteristics of Debaters for Predicting Persuasiveness.
Khalid Al-Khatib, Michael Völske, Shahbaz Syed, Nikolay Kolyada, and Benno Stein. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 7067–7072, 2020. [paper][bib]
ACL 2020a. Pairwise Annotation of Argument Quality.
Lukas Gienapp, Benno Stein, Matthias Hagen, and Martin Potthast. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 5772–5781, 2020. [paper][bib]
CHIIR 2020. Investigating Expectations for Voice-based and Conversational Argument Search on the Web.
Johannes Kiesel, Kevin Lang, Henning Wachsmuth, Eva Hornecker, and Benno Stein. In Proceedings of the 2020 ACM SIGIR Conference on Human Information Interaction & Retrieval, pages 53–62, 2020. [paper]
ECIR 2020. Touché: First Shared Task on Argument Retrieval.
Alexander Bondarenko, Matthias Hagen, Martin Potthast, Henning Wachsmuth, Meriem Beloucif, Chris Biemann, Alexander Panchenko, and Benno Stein. In Proceedings of the 42nd European Conference on Information Retrieval, pages 517–523, 2020. [paper]
AAAI 2020. End-to-End Argumentation Knowledge Graph Construction.
Khalid Al-Khatib, Yufang Hou, Henning Wachsmuth, Charles Jochim, Francesca Bonin, and Benno Stein. In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, pages 7367–7374, 2020. [paper]
2019
EMNLP-IJCNLP 2019. Modeling Frames in Argumentation.
Yamen Ajjour, Milad Alshomary, Henning Wachsmuth, and Benno Stein. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, pages 2915–2925, 2019. [paper][bib]
INLG 2019. Computational Argumentation Synthesis as a Language Modeling Task.
Roxanne El Baff, Henning Wachsmuth, Khalid Al-Khatib, Manfred Stede, and Benno Stein. In Proceedings of the 12th International Conference on Natural Language Generation, pages 54–64, 2019. [paper][bib]
CL 2019. Book Review of ”Argumentation Mining”.
Henning Wachsmuth. Computational Linguistics 45(3), pages 603–606, 2019. [paper][bib]
KI 2019. Data Acquisition for Argument Search: The args.me Corpus.
Yamen Ajjour, Henning Wachsmuth, Johannes Kiesel, Martin Potthast, Matthias Hagen and Benno Stein. In Proceedings of the 42nd Edition of the German Conference on Artificial Intelligence, pages 48–59, 2019. Best Paper Award [paper][bib]
ArgMining 2019b. Proceedings of the 6th Workshop on Argument Mining.
Benno Stein and Henning Wachsmuth. Association for Computational Linguistics, 2019. [proceedings][bib]
ArgMining 2019a. Categorizing Comparative Sentences.
Alexander Panchenko, Alexander Bondarenko, Mirco Franzek, Matthias Hagen, and Chris Biemann. In Proceedings of the 6th Workshop on Argument Mining, pages 136–145, 2019. [paper][bib]
ACL 2019. TARGER: Neural Argument Mining at Your Fingertips.
Artem Chernodub, Oleksiy Oliynyk, Philipp Heidenreich, Alexander Bondarenko, Matthias Hagen, Chris Biemann, and Alexander Panchenko. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pages 195–200, 2019. [paper][bib]
SIGIR 2019. Argument Search: Assessing Argument Relevance.
Martin Potthast, Lukas Gienapp, Florian Euchner, Nick Heilenkötter, Nico Weidmann, Henning Wachsmuth, Benno Stein, and Matthias Hagen. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 1117–1120, 2019. [paper] [bib]
CHIIR 2019. Answering Comparative Questions: Better than Ten-Blue-Links?
Matthias Schildwächter, Alexander Bondarenko, Julian Zenker, Matthias Hagen, Chris Biemann, and Alexander Panchenko. In Proceedings of the 2019 Conference on Human Information Interaction & Retrieval, pages 361–365, 2019. [paper]
2018
INLG 2018. Learning to Flip the Bias of News Headlines.
Wei-Fan Chen, Henning Wachsmuth, Khalid Al-Khatib, and Benno Stein. In Proceedings of the 11th International Conference on Natural Language Generation, pages 79–88, 2018. [paper] [bib]
EMNLP 2018. Visualization of the Topic Space of Argument Search Results in args.me.
Yamen Ajjour, Henning Wachsmuth, Dora Kiesel, Patrick Riehmann, Fan Fan, Giuliano Castiglia, Rosemary Adejoh, Bernd Fröhlich, and Benno Stein. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 60–65, 2018. [paper] [bib] [demo]
CoNLL 2018. Challenge or Empower: Revisiting Argumentation Quality in a News Editorial Corpus.
Roxanne El Baff, Henning Wachsmuth, Khalid Al-Khatib, and Benno Stein. In Proceedings of the 22nd Conference on Computational Natural Language Learning, pages 454–464, 2018. [paper] [bib] [poster]
COLING 2018. Argumentation Synthesis following Rhetorical Strategies.
Henning Wachsmuth, Manfred Stede, Roxanne El Baff, Khalid Al-Khatib, Maria Skeppstedt, and Benno Stein. In Proceedings of the 27th International Conference on Computational Linguistics, pages 3753–3765, August 2018. [paper] [bib] [poster]
ACL 2018b. Retrieval of the Best Counterargument without Prior Topic Knowledge.
Henning Wachsmuth, Shahbaz Syed, and Benno Stein. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pages 241–251, July 2018. [paper] [supplementary] [bib] [slides] [video]
ACL 2018a. Modeling Deliberative Argumentation Strategies on Wikipedia.
Khalid Al-Khatib, Henning Wachsmuth, Kevin Lang, Jakob Herpel, Matthias Hagen, and Benno Stein. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pages 2545–2555, July 2018. [paper] [bib] [poster]
SemEval 2018. SemEval-2018 Task 12: The Argument Reasoning Comprehension Task.
Ivan Habernal, Henning Wachsmuth, Iryna Gurevych, and Benno Stein. In Proceedings of the 11th International Workshop on Semantic Evaluation, pages 763–772, June 2018. [paper] [bib]
NAACL 2018b. Before Name-calling: Dynamics and Triggers of Ad Hominem Fallacies in Web Argumentation.
Ivan Habernal, Henning Wachsmuth, Iryna Gurevych, and Benno Stein. In Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 386–396, June 2018. [paper] [bib]
NAACL 2018a. The Argument Reasoning Comprehension Task: Identification and Reconstruction of Implicit Warrants.
Ivan Habernal, Henning Wachsmuth, Iryna Gurevych, and Benno Stein. In Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 1930–1940, June 2018. [paper] [bib]
2017
EMNLP 2017b. The Impact of Modeling Overall Argumentation with Tree Kernels.
Henning Wachsmuth, Giovanni Da San Martino, Dora Kiesel, and Benno Stein. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 2369–2379, September 2017. [paper] [bib] [slides] [video]
EMNLP 2017a. Patterns of Argumentation Strategies across Topics.
Khalid Al-Khatib, Henning Wachsmuth, Matthias Hagen, and Benno Stein. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 1362–1368, September 2017. [paper] [bib]
ArgMining 2017b. Building an Argument Search Engine for the Web.
Henning Wachsmuth, Martin Potthast, Khalid Al-Khatib, Yamen Ajjour, Jana Puschmann, Jiani Qu, Jonas Dorsch, Viorel Morari, Janek Bevendorff, and Benno Stein. In Proceedings of the Fourth Workshop on Argument Mining, pages 49–59, September 2017. [paper] [bib] [slides]
ArgMining 2017a. Unit Segmentation of Argumentative Texts.
Yamen Ajjour, Wei-Fan Chen, Johannes Kiesel, Henning Wachsmuth, and Benno Stein. In Proceedings of the Fourth Workshop on Argument Mining, pages 118–128, September 2017. [paper] [bib]
ACL 2017. Argumentation Quality Assessment: Theory vs. Practice.
Henning Wachsmuth, Nona Naderi, Ivan Habernal, Yufang Hou, Graeme Hirst, Iryna Gurevych, and Benno Stein. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pages 250–255, August 2017. [paper] [bib] [poster]
ACM TOIT 2017. A Universal Model for Discourse-Level Argumentation Analysis.
Henning Wachsmuth and Benno Stein. Special Section of the ACM Transactions on Internet Technology: Argumentation in Social Media, 17 (3) : 28:1–28:24, June 2017. [paper] [bib]
EACL 2017b. Computational Argumentation Quality Assessment in Natural Language.
Henning Wachsmuth, Nona Naderi, Yufang Hou, Yonatan Bilu, Vinodkumar Prabhakaran, Tim Alberdingk Thijm, Graeme Hirst, and Benno Stein. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, pages 176–187, April 2017. [paper] [bib] [slides]
EACL 2017a. “PageRank” for Argument Relevance.
Henning Wachsmuth, Benno Stein, and Yamen Ajjour. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, pages 1116–1126, April 2017. [paper] [bib] [slides]
2016
COLING 2016b. Using Argument Mining to Assess the Argumentation Quality of Essays.
Henning Wachsmuth, Khalid Al-Khatib, and Benno Stein. In Proceedings of the 26th International Conference on Computational Linguistics, pages 1680–1692, December 2016. [paper] [bib] [poster]
COLING 2016a. A News Editorial Corpus for Mining Argumentation Strategies.
Khalid Al-Khatib, Henning Wachsmuth, Johannes Kiesel, Matthias Hagen, and Benno Stein. In Proceedings of the 26th International Conference on Computational Linguistics, pages 3433–3443, December 2016. [paper] [bib]
NAACL 2016. Cross-Domain Mining of Argumentative Text through Distant Supervision.
Khalid Al-Khatib, Henning Wachsmuth, Matthias Hagen, Jonas Köhler, and Benno Stein. In Proceedings of the 15th Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 1395–1404, June 2016. [paper] [bib]
2015
EMNLP 2015. Sentiment Flow — A General Model of Web Review Argumentation.
Henning Wachsmuth, Johannes Kiesel, and Benno Stein. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pages 601–611, September 2015. [paper] [bib] [slides] [video]
LNCS 9383. Text Analysis Pipelines — Towards Ad-hoc Large-scale Text Mining.
Henning Wachsmuth. Springer, 2015. ISBN 978-3-319-25740-2. [preprint] [book] [bib]
ArgMining 2015. A Shared Task on Argumentation Mining in Newspaper Editorials.
Johannes Kiesel, Khalid Al-Khatib, Matthias Hagen, and Benno Stein. In Proceedings of the 2nd Workshop on Argumentation Mining, pages 35–38, June 2015. [paper] [bib]
2014
COLING 2014. Modeling Review Argumentation for Robust Sentiment Analysis.
Henning Wachsmuth, Martin Trenkmann, Benno Stein, and Gregor Engels. In Proceedings of the 25th International Conference on Computational Linguistics, pages 553–564, August 2014. [paper] [bib] [poster]
CICLing 2014. A Review Corpus for Argumentation Analysis.
Henning Wachsmuth, Martin Trenkmann, Benno Stein, Gregor Engels, and Tsvetomira Palakarska. In Proceedings of the 15th International Conference on Intelligent Text Processing and Computational Linguistics, pages 115–127, April 2014. Best Presentation Award. [paper] [bib] [slides]