Stein, Benno, and Henning Wachsmuth, editors. Proceedings of the 6th Workshop on Argument Mining. Association for Computational Linguistics, 2019.
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El Baff, Roxanne, et al. “Computational Argumentation Synthesis as a Language Modeling Task.” Proceedings of the 12th International Conference on Natural Language Generation, Association for Computational Linguistics, 2019, pp. 54–64.
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Alshomary, Milad, et al. “Wikipedia Text Reuse: Within and Without.” Advances in Information Retrieval, edited by Leif Azzopardi et al., Springer International Publishing, 2019, pp. 747–54.
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Chen, Wei-Fan, et al. “Unraveling the Search Space of Abusive Language in Wikipedia with Dynamic Lexicon Acquisition.” Proceedings of the Second Workshop on Natural Language Processing for Internet Freedom, 2019, pp. 76–82.
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Habernal, Ivan, et al. “The Argument Reasoning Comprehension Task: Identification and Reconstruction of Implicit Warrants.” Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018, pp. 1930–1940.
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Al Khatib, Khalid, et al. “Modeling Deliberative Argumentation Strategies on Wikipedia.” Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2018, pp. 2545–55.
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Habernal, Ivan, et al. “Before Name-Calling: Dynamics and Triggers of Ad Hominem Fallacies in Web Argumentation.” Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), 2018, pp. 386–96.
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Habernal, Ivan, et al. “SemEval-2018 Task 12: The Argument Reasoning Comprehension Task.” Proceedings of The 12th International Workshop on Semantic Evaluation, 2018, pp. 763–72.
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Wachsmuth, Henning, et al. “Retrieval of the Best Counterargument without Prior Topic Knowledge.” Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2018, pp. 241–51.
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Wachsmuth, Henning, et al. “Argumentation Synthesis Following Rhetorical Strategies.” Proceedings of the 27th International Conference on Computational Linguistics, 2018, pp. 3753–65.
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Ajjour, Yamen, et al. “Visualization of the Topic Space of Argument Search Results in Args. Me.” Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, 2018, pp. 60–65.
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El Baff, Roxanne, et al. “Challenge or Empower: Revisiting Argumentation Quality in a News Editorial Corpus.” Proceedings of the 22nd Conference on Computational Natural Language Learning, Association for Computational Linguistics, 2018, pp. 454–64.
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Chen, Wei-Fan, and Lun-Wei Ku. “We Like, We Post: A Joint User-Post Approach for Facebook Post Stance Labeling.” IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 10, IEEE, 2018, pp. 2013–23.
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Chen, Mei-Hua, et al. “Application of Sentiment Analysis to Language Learning.” IEEE Access, vol. 6, IEEE, 2018, pp. 24433–42.
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Chen Wei-Fan, and Ku Lun-Wei. “N2d`c5fŠ9efNf6 CSentiPackage c\55ac9.” ff8[78Œc7Š0ayd1[78, bzcbSf0^2b{c4[78ff8Œc7Š0a[78z76, 2018.
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Kiesel, Johannes, et al. “Reproducible Web Corpora.”10.1145/3239574__Journal of Data and Information Quality, 2018, pp. 1–25, doi:10.1145/3239574.
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Chen, Wei-Fan, et al. “Learning to Flip the Bias of News Headlines.” Proceedings of the 11th International Conference on Natural Language Generation, Association for Computational Linguistics, 2018, pp. 79–88.
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Chen, Wei-Fan, et al. “A User Study on Snippet Generation: Text Reuse vs. Paraphrases.” Proceedings of the 41st International ACM SIGIR Conference on Research &; Development in Information Retrieval, 2018, pp. 1033–36.
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Potthast, Martin, et al. “A Plan for Ancillary Copyright: Original Snippets.” Proceedings of the Second International Workshop on Recent Trends in News Information Retrieval, 2018, pp. 3–5.
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Ajjour, Yamen, et al. “Unit Segmentation of Argumentative Texts.” Proceedings of the 4th Workshop on Argument Mining, 2017, pp. 118–28.
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Al Khatib, Khalid, et al. “Patterns of Argumentation Strategies across Topics.” Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017, pp. 1362–68.
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Kiesel, Johannes, et al. “WAT-SL: A Customizable Web Annotation Tool for Segment Labeling.” Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics, 2017, pp. 13–16.
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Wachsmuth, Henning, et al. “‘Page Rank’’’ for Argument Relevance.’” Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, 2017, pp. 1117–27.
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Wachsmuth, Henning, et al. “Building an Argument Search Engine for the Web.” Proceedings of the 4th Workshop on Argument Mining, 2017, pp. 49–59.
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Wachsmuth, Henning, et al. “The Impact of Modeling Overall Argumentation with Tree Kernels.” Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017, pp. 2369–79.
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Wachsmuth, Henning, et al. “Computational Argumentation Quality Assessment in Natural Language.” Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, 2017, pp. 176–87.
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Wachsmuth, Henning, and Benno Stein. “A Universal Model for Discourse-Level Argumentation Analysis.” Special Section of the ACM Transactions on Internet Technology: Argumentation in Social Media, no. 3, 2017, pp. 1–24.
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Wachsmuth, Henning, et al. “Argumentation Quality Assessment: Theory vs. Practice.”10.18653/v1/P17-2039__Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2017, pp. 250–55, doi:10.18653/v1/P17-2039.
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Hagen, Matthias, et al. “Webis at the CLEF 2017 Dynamic Search Lab.” Working Notes of CLEF 2017 - Conference and Labs of the Evaluation Forum, 2017.
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Chen, Wei-Fan, et al. “How to Get Endorsements? Predicting Facebook Likes Using Post Content and User Engagement.” International Conference on HCI in Business, Government, and Organizations, 2017, pp. 190–202.
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Al Khatib, Khalid, et al. “A News Editorial Corpus for Mining Argumentation Strategies.” Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, 2016, pp. 3433–43.
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Al-Khatib, Khalid, et al. “Cross-Domain Mining of Argumentative Text through Distant Supervision.”10.18653/v1/N16-1165__Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2016, pp. 1395–404, doi:10.18653/v1/N16-1165.
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DOI: 10.18653/v1/N16-1165

Wachsmuth, Henning, et al. “Using Argument Mining to Assess the Argumentation Quality of Essays.” Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, 2016, pp. 1680–91.
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Wachsmuth, Henning. “Pipelines Für Effiziente Und Robuste Ad-Hoc Textanalyse.” Ausgezeichnete Informatikdissertationen 2015, 2016, pp. 329–38.
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Chen, Wei-Fan, and Lun-Wei Ku. “UTCNN: A Deep Learning Model of Stance Classification on Social Media Text.” Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics, 2016, pp. 1635–45.
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Chen, Wei-Fan, et al. “WordForce: Visualizing Controversial Words in Debates.” Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations, 2016, pp. 273–77.
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Ku, Lun-Wei, and Wei-Fan Chen. “Chinese Textual Sentiment Analysis: Datasets, Resources and Tools.” Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Tutorial Abstracts, 2016, pp. 5–8.
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Wachsmuth, Henning, et al. “Sentiment Flow - A General Model of Web Review Argumentation.”10.18653/v1/D15-1072__Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, edited by Junichi Tsujii and Jan Hajic, 2015, pp. 601–11, doi:10.18653/v1/D15-1072.
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DOI: 10.18653/v1/D15-1072

Wachsmuth, Henning. Text Analysis Pipelines - Towards Ad-Hoc Large-Scale Text Mining. 2015, doi:http://dx.doi.org/10.1007/978-3-319-25741-9.
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Wachsmuth, Henning. Pipelines for Ad-Hoc Large-Scale Text Mining. 2015.
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Chen, Wei-Fan, et al. “Embarrassed or Awkward? Ranking Emotion Synonyms for ESL Learners’ Appropriate Wording.” Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications, 2015, pp. 144–53.
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Chen, Wei-Fan, et al. “Mining Supportive and Unsupportive Evidence from Facebook Using Anti-Reconstruction of the Nuclear Power Plant as an Example.” 2015 AAAI Spring Symposium Series, 2015.
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Chen, Wei-Fan, et al. “Topic-Based Stance Mining for Social Media Texts.” International Conference on HCI in Business, 2015, pp. 22–33.
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Chen, Wei-Fan, et al. “A Computer-Assistance Learning System for Emotional Wording.” IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 5, IEEE, 2015, pp. 1093–104.
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Chen, Mei-Hua, et al. “Technology Enhanced Emotion Expression Learning.” Proceedings of the Sixth Joint Foreign Language Education and Technology Conference (FLEAT VI), 2015.
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Wachsmuth, Henning, et al. “A Review Corpus for Argumentation Analysis.” Proceedings of the 15th International Conference on Intelligent Text Processing and Computational Linguistics, 2014, pp. 115–127.
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Brüseke, Frank, et al. “PBlaman: Performance Blame Analysis Based on Palladio Contracts.” Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment, no. 12, 2014, pp. 1975–2004.
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Wachsmuth, Henning, et al. “Modeling Review Argumentation for Robust Sentiment Analysis.” Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers, 2014, pp. 553–64.
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Abu Quba Rana, Chamsi, et al. “ISoNTRE: The Social Network Transformer into Recommendation Engine.” 2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA), 2014, pp. 169–75.
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Chen, Mei-Hua, et al. “RESOLVE: An Emotion Word Suggestion System Facilitates Language Learners’ Emotional Expressions.” Proceedings of the AsiaCALL 2014, 2014.
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