TY - CONF AU - Alshomary, Milad AU - El Baff, Roxanne AU - Gurcke, Timon AU - Wachsmuth, Henning ID - 30840 T2 - Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics TI - The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments ER - TY - CONF AU - Wachsmuth, Henning AU - Alshomary, Milad ID - 33004 T2 - Proceedings of the 29th International Conference on Computational Linguistics TI - "Mama Always Had a Way of Explaining Things So I Could Understand": A Dialogue Corpus for Learning How to Explain ER - TY - JOUR AU - Lauscher, Anne AU - Wachsmuth, Henning AU - Gurevych, Iryna AU - Glavaš, Goran ID - 34049 JF - Transactions of the Association for Computational Linguistics TI - On the Role of Knowledge in Computational Argumentation ER - TY - CONF AU - Kiesel, Johannes AU - Alshomary, Milad AU - Handke, Nicolas AU - Cai, Xiaoni AU - Wachsmuth, Henning AU - Stein, Benno ID - 22157 T2 - Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics TI - Identifying the Human Values behind Arguments ER - TY - CONF AB - News articles both shape and reflect public opinion across the political spectrum. Analyzing them for social bias can thus provide valuable insights, such as prevailing stereotypes in society and the media, which are often adopted by NLP models trained on respective data. Recent work has relied on word embedding bias measures, such as WEAT. However, several representation issues of embeddings can harm the measures' accuracy, including low-resource settings and token frequency differences. In this work, we study what kind of embedding algorithm serves best to accurately measure types of social bias known to exist in US online news articles. To cover the whole spectrum of political bias in the US, we collect 500k articles and review psychology literature with respect to expected social bias. We then quantify social bias using WEAT along with embedding algorithms that account for the aforementioned issues. We compare how models trained with the algorithms on news articles represent the expected social bias. Our results suggest that the standard way to quantify bias does not align well with knowledge from psychology. While the proposed algorithms reduce the~gap, they still do not fully match the literature. AU - Spliethöver, Maximilian AU - Keiff, Maximilian AU - Wachsmuth, Henning ID - 34047 T2 - Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022) TI - No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media ER - TY - CONF AU - Sengupta, Meghdut AU - Alshomary, Milad AU - Wachsmuth, Henning ID - 34067 T2 - Proceedings of the 2022 Workshop on Figurative Language Processing TI - Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning ER - TY - CHAP AU - Bondarenko, Alexander AU - Fröbe, Maik AU - Kiesel, Johannes AU - Syed, Shahbaz AU - Gurcke, Timon AU - Beloucif, Meriem AU - Panchenko, Alexander AU - Biemann, Chris AU - Stein, Benno AU - Wachsmuth, Henning AU - Potthast, Martin AU - Hagen, Matthias ID - 34077 SN - 0302-9743 T2 - Lecture Notes in Computer Science TI - Overview of Touché 2022: Argument Retrieval ER - TY - CONF AU - Chen, Wei-Fan AU - Chen, Mei-Hua AU - Mudgal, Garima AU - Wachsmuth, Henning ID - 33274 T2 - Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022) TI - Analyzing Culture-Specific Argument Structures in Learner Essays ER - TY - CONF AU - Alshomary, Milad AU - Rieskamp, Jonas AU - Wachsmuth, Henning ID - 32247 T2 - Proceedings of the 9th International Conference on Computational Models of Argument TI - Generating Contrastive Snippets for Argument Search ER - TY - GEN AU - Chen, Mei-Hua AU - Mudgal, Garima AU - Chen, Wei-Fan AU - Wachsmuth, Henning ID - 31068 T2 - EUROCALL TI - Investigating the argumentation structures of EFL learners from diverse language backgrounds ER - TY - GEN AB - This thesis aims to provide a bidirectional chatbot solution for the requirement engineering process. The Sonderforschungsbereich (SFB) 901 intends to provide the composition of software service On-the-Fly (OTF). The sub-project (B1) of the SFB 901 project deals with the parameters of service configuration. OTF Computing aims to eradicate the dependency on the requirement engineers for the software development process. However, there is no existing bidirectional chatbot solution that analyses user software requirements and provides viable suggestions to the user regarding their service. Previously, CORDULA chatbot was developed to analyze the software requirements but cannot keep the conversation’s context. The Rasa framework is integrated with the knowledge base to solve the issue, the knowledge base provides domain-specific knowledge to the chatbot. The software description is passed through the natural language understanding process to give consciousness to the chatbot. This process involves various machine learning models, including app family classification, to correctly identify the domain for user OTF service. The statistical models like naïve Bayes, kNN and SVM are compared with transformer models for this classification task. Furthermore, the entities (functional requirements) are also separated from the user description. The chatbot provides the suggestion of requirements from the preliminary service template with the support of the knowledge base. Furthermore, the generated response is compared with the state-of-the-art DialoGPT transformer model and ChatterBot conversational library. These models are trained over the software development related conversational dataset. All the responses are ranked using the DialoRPT model, and the BLEU score to evaluates the models’ responses. Moreover, the chatbot mod- els are tested with human participants, they used and scored the chatbot responses based on effectiveness, efficiency and satisfaction. The overall response accuracy is also measured by averaging the user approval over the generated responses. AU - Ahmed, Mobeen ID - 29000 TI - Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing ER - TY - GEN AU - Palushi, Juela ID - 45790 TI - Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks ER - TY - GEN AU - Budanurmath, Vinaykumar ID - 45789 TI - Propaganda Technique Detection Using Connotation Frames ER - TY - CONF AU - Skitalinskaya, Gabriella AU - Klaff, Jonas AU - Wachsmuth, Henning ID - 20115 T2 - Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics TI - Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale ER - TY - CONF AU - Bondarenko, Alexander AU - Gienapp, Lukas AU - Fröbe, Maik AU - Beloucif, Meriem AU - Ajjour, Yamen AU - Panchenko, Alexander AU - Biemann, Chris AU - Stein, Benno AU - Wachsmuth, Henning AU - Potthast, Martin AU - Hagen, Matthias ID - 3774 T2 - Proceedings of the 43rd annual European Conference on Information Retrieval Research TI - Overview of Touché 2021: Argument Retrieval ER - TY - CONF AU - Nouri, Zahra AU - Gadiraju, Ujwal AU - Engels, Gregor AU - Wachsmuth, Henning ID - 23708 T2 - Proceedings of the 32nd ACM Conference on Hypertext and Social Media TI - What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing ER - TY - CONF AB - Word embedding models reflect bias towards genders, ethnicities, and other social groups present in the underlying training data. Metrics such as ECT, RNSB, and WEAT quantify bias in these models based on predefined word lists representing social groups and bias-conveying concepts. How suitable these lists actually are to reveal bias - let alone the bias metrics in general - remains unclear, though. In this paper, we study how to assess the quality of bias metrics for word embedding models. In particular, we present a generic method, Bias Silhouette Analysis (BSA), that quantifies the accuracy and robustness of such a metric and of the word lists used. Given a biased and an unbiased reference embedding model, BSA applies the metric systematically for several subsets of the lists to the models. The variance and rate of convergence of the bias values of each model then entail the robustness of the word lists, whereas the distance between the models' values gives indications of the general accuracy of the metric with the word lists. We demonstrate the behavior of BSA on two standard embedding models for the three mentioned metrics with several word lists from existing research. AU - Spliethöver, Maximilian AU - Wachsmuth, Henning ID - 22156 T2 - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21 TI - Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models ER - TY - CONF AU - Syed, Shahbaz AU - Al-Khatib, Khalid AU - Alshomary, Milad AU - Wachsmuth, Henning AU - Potthast, Martin ID - 22158 T2 - 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 (ACL-IJCNLP 2021): Findings TI - Generating Informative Conclusions for Argumentative Texts ER - TY - CONF AU - Barrow, Joe AU - Jain, Rajiv AU - Lipka, Nedim AU - Dernoncourt, Franck AU - Morariu, Vlad AU - Manjunatha, Varun AU - Oard, Douglas AU - Resnik, Philip AU - Wachsmuth, Henning ID - 22159 T2 - 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 (ACL-IJCNLP 2021) TI - Syntopical Graphs for Computational Argumentation Tasks ER - TY - CONF AU - Al-Khatib, Khalid AU - Trautner, Lukas AU - Wachsmuth, Henning AU - Hou, Yufang AU - Stein, Benno ID - 22160 T2 - 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 (ACL-IJCNLP 2021) TI - Employing Argumentation Knowledge Graphs for Neural Argument Generation ER - TY - CONF AU - Kiesel, Johannes AU - Spina, Damiano AU - Wachsmuth, Henning AU - Stein, Benno ID - 22448 T2 - Proceedings of the 2021 Conversational User Interfaces Conference TI - The Meant, the Said, and the Understood: Conversational Argument Search and Cognitive Biases ER - TY - CONF AU - Alshomary, Milad AU - Gurcke, Timon AU - Syed, Shahbaz AU - Heinisch, Philipp AU - Spliethöver, Maximilian AU - Cimiano, Philipp AU - Potthast, Martin AU - Wachsmuth, Henning ID - 25297 T2 - Proceedings of the 8th Workshop on Argument Mining TI - Key Point Analysis via Contrastive Learning and Extractive Argument Summarization ER - TY - CONF AU - Nouri, Zahra AU - Prakash, Nikhil AU - Gadiraju, Ujwal AU - Wachsmuth, Henning ID - 25294 T2 - Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2021 TI - iClarify - A Tool to Help Requesters Iteratively Improve Task Descriptions in Crowdsourcing ER - TY - CONF AU - Gurcke, Timon AU - Alshomary, Milad AU - Wachsmuth, Henning ID - 25295 T2 - Proceedings of the 8th Workshop on Argument Mining TI - Assessing the Sufficiency of Arguments through Conclusion Generation ER - TY - CONF AB - When engaging in argumentative discourse, skilled human debaters tailor claims to the beliefs of the audience, to construct effective arguments. Recently, the field of computational argumentation witnessed extensive effort to address the automatic generation of arguments. However, existing approaches do not perform any audience-specific adaptation. In this work, we aim to bridge this gap by studying the task of belief-based claim generation: Given a controversial topic and a set of beliefs, generate an argumentative claim tailored to the beliefs. To tackle this task, we model the people's prior beliefs through their stances on controversial topics and extend state-of-the-art text generation models to generate claims conditioned on the beliefs. Our automatic evaluation confirms the ability of our approach to adapt claims to a set of given beliefs. In a manual study, we additionally evaluate the generated claims in terms of informativeness and their likelihood to be uttered by someone with a respective belief. Our results reveal the limitations of modeling users' beliefs based on their stances, but demonstrate the potential of encoding beliefs into argumentative texts, laying the ground for future exploration of audience reach. AU - Alshomary, Milad AU - Chen, Wei-Fan AU - Gurcke, Timon AU - Wachsmuth, Henning ID - 21178 T2 - Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume TI - Belief-based Generation of Argumentative Claims ER - TY - CONF AU - Chen, Wei-Fan AU - Al Khatib, Khalid AU - Stein, Benno AU - Wachsmuth, Henning ID - 23709 T2 - Findings of the Association for Computational Linguistics: EMNLP 2021 TI - Controlled Neural Sentence-Level Reframing of News Articles ER - TY - CONF AU - Alshomary, Milad AU - Syed, Shahbaz AU - Potthast, Martin AU - Wachsmuth, Henning ID - 22229 T2 - 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 (ACL-IJCNLP 2021) TI - Argument Undermining: Counter-Argument Generation by Attacking Weak Premises ER - TY - GEN AU - Bülling, Jonas ID - 45788 TI - Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump ER - TY - GEN AU - Mishra, Avishek ID - 45787 TI - Computational Text Professionalization using Neural Sequence-to-Sequence Models ER - TY - CONF AU - Nouri, Zahra AU - Wachsmuth, Henning AU - Engels, Gregor ID - 20116 T2 - Proceedings of COLING 2020, the 28th International Conference on Computational Linguistics TI - Mining Crowdsourcing Problems from Discussion Forums of Workers ER - TY - CONF AU - El Baff, Roxanne AU - Al-Khatib, Khalid AU - Stein, Benno AU - Wachsmuth, Henning ID - 20122 T2 - Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotions in Social Media (PEOPLES 2020) TI - Persuasiveness of News Editorials depending on Ideology and Personality ER - TY - CONF AU - Spliethöver, Maximilian AU - Wachsmuth, Henning ID - 20139 T2 - Proceedings of the 7th Workshop on Argument Mining (ArgMining 2020) TI - Argument from Old Man's View: Assessing Social Bias in Argumentation ER - TY - CONF AU - Dorsch, Jonas AU - Wachsmuth, Henning ID - 20140 T2 - Proceedings of the 7th Workshop on Argument Mining (ArgMining 2020) TI - Semi-Supervised Cleansing of Web Argument Corpora ER - TY - CONF AU - Bondarenko, Alexander AU - Fröbe, Maik AU - Beloucif, Meriem AU - Gienapp, Lukas AU - Ajjour, Yamen AU - Panchenko, Alexander AU - Biemann, Chris AU - Stein, Benno AU - Wachsmuth, Henning AU - Potthast, Martin AU - Hagen, Matthias ID - 20166 T2 - CEUR Workshop Proceedings TI - Overview of Touché 2020: Argument Retrieval VL - 2696 ER - TY - CONF AU - Wachsmuth, Henning AU - Werner, Till ID - 3800 T2 - Proceedings of COLING 2020, the 28th International Conference on Computational Linguistics TI - Intrinsic Quality Assessment of Arguments ER - TY - CONF AU - El Baff, Roxanne AU - Wachsmuth, Henning AU - Al-Khatib, Khalid AU - Stein, Benno ED - Tsujii, Junichi ED - Hajic, Jan ID - 3878 T2 - Proceedings of 58th Annual Meeting of the Association for Computational Linguistics TI - Analyzing the Persuasive Effect of Style in News Editorial Argumentation ER - TY - CONF AU - Alshomary, Milad AU - Düsterhus, Nick AU - Wachsmuth, Henning ID - 7283 T2 - Proceedings of 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval TI - Extractive Snippet Generation for Arguments ER - TY - CONF AU - Al-Khatib, Khalid AU - Hou, Yufang AU - Wachsmuth, Henning AU - Jochim, Charles AU - Bonin, Francesca AU - Stein, Benno ID - 15820 T2 - Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020) TI - End-to-End Argumentation Knowledge Graph Construction ER - TY - CONF AU - Bondarenko, Alexander AU - Hagen, Matthias AU - Potthast, Martin AU - Wachsmuth, Henning AU - Beloucif, Meriem AU - Biemann, Chris AU - Panchenko, Alexander AU - Stein, Benno ID - 15821 T2 - Proceedings of the 42nd European Conference on Information Retrieval (ECIR 2020) TI - Touché: First Shared Task on Argument Retrieval ER - TY - CONF AU - Kiesel, Johannes AU - Lang, Kevin AU - Wachsmuth, Henning AU - Hornecker, Eva AU - Stein, Benno ID - 15825 T2 - Proceedings of the 2020 ACM SIGIR Conference on Human Information Interaction & Retrieval (CHIIR 2020) TI - Investigating Expectations for Voice-based and Conversational Argument Search on the Web ER - TY - JOUR AU - Kiesel, Dora AU - Riehmann, Patrick AU - Wachsmuth, Henning AU - Stein, Benno AU - Fröhlich, Bernd ID - 10330 IS - 2 JF - IEEE Transactions of Visualization & Computer Graphics TI - Visual Analysis of Argumentation in Essays VL - 27 ER - TY - CONF AU - Chen, Wei-Fan AU - Al-Khatib, Khalid AU - Wachsmuth, Henning AU - Stein, Benno ID - 3776 T2 - Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science TI - Analyzing Political Bias and Unfairness in News Articles at Different Levels of Granularity ER - TY - CONF AU - Syed, Shahbaz AU - Chen, Wei-Fan AU - Hagen, Matthias AU - Stein, Benno AU - Wachsmuth, Henning AU - Potthast, Martin ID - 20137 T2 - Proceedings of the 13th International Conference on Natural Language Generation (INLG 2020) TI - Task Proposal: Abstractive Snippet Generation for Web Pages ER - TY - CONF AU - Chen, Wei-Fan AU - Al-Khatib, Khalid AU - Stein, Benno AU - Wachsmuth, Henning ID - 3818 T2 - Findings of the Association for Computational Linguistics: EMNLP 2020 TI - Detecting Media Bias in News Articles using Gaussian Bias Distributions ER - TY - CONF AU - Chen, Wei-Fan AU - Syed, Shahbaz AU - Stein, Benno AU - Hagen, Matthias AU - Potthast, Martin ID - 15826 T2 - Proceedings of the Web Conference 2020 TI - Abstractive Snippet Generation ER - TY - CONF AU - Alshomary, Milad AU - Syed, Shahbaz AU - Potthast, Martin AU - Wachsmuth, Henning ID - 16868 T2 - Proceedings of 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020) TI - Target Inference in Argument Conclusion Generation ER - TY - CONF AU - Potthast, Martin AU - Gienapp, Lukas AU - Euchner, Florian AU - Heilenkötter, Nick AU - Weidmann, Nico AU - Wachsmuth, Henning AU - Stein, Benno AU - Hagen, Matthias ID - 11709 T2 - 42nd International ACM Conference on Research and Development in Information Retrieval (SIGIR 2019) TI - Argument Search: Assessing Argument Relevance ER - TY - GEN AU - Wachsmuth, Henning ID - 11713 IS - 3 T2 - Computational Linguistics TI - Book Review: Argumentation Mining VL - 45 ER - TY - CONF AU - Ajjour, Yamen AU - Wachsmuth, Henning AU - Kiesel, Johannes AU - Potthast, Martin AU - Hagen, Matthias AU - Stein, Benno ID - 11714 T2 - Proceedings of the 42nd Edition of the German Conference on Artificial Intelligence TI - Data Acquisition for Argument Search: The args.me Corpus ER - TY - CONF AU - Ajjour, Yamen AU - Alshomary, Milad AU - Wachsmuth, Henning AU - Stein, Benno ID - 12931 T2 - Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing TI - Modeling Frames in Argumentation ER - TY - GEN ED - Stein, Benno ED - Wachsmuth, Henning ID - 15235 TI - Proceedings of the 6th Workshop on Argument Mining ER - TY - CONF AU - El Baff, Roxanne AU - Wachsmuth, Henning AU - Al-Khatib, Khalid AU - Stede, Manfred AU - Stein, Benno ID - 13144 T2 - Proceedings of the 12th International Conference on Natural Language Generation TI - Computational Argumentation Synthesis as a Language Modeling Task ER - TY - CONF AB - 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. AU - Alshomary, Milad AU - Völske, Michael AU - Licht, Tristan AU - Wachsmuth, Henning AU - Stein, Benno AU - Hagen, Matthias AU - Potthast, Martin ED - Azzopardi, Leif ED - Stein, Benno ED - Fuhr, Norbert ED - Mayr, Philipp ED - Hauff, Claudia ED - Hiemstra, Djoerd ID - 10284 SN - 978-3-030-15712-8 T2 - Advances in Information Retrieval TI - Wikipedia Text Reuse: Within and Without ER - TY - CONF AU - Chen, Wei-Fan AU - Al-Khatib, Khalid AU - Hagen, Matthias AU - Wachsmuth, Henning AU - Stein, Benno ID - 13259 T2 - Proceedings of the Second Workshop on Natural Language Processing for Internet Freedom TI - Unraveling the Search Space of Abusive Language in Wikipedia with Dynamic Lexicon Acquisition ER - TY - CONF AU - Habernal, Ivan AU - Wachsmuth, Henning AU - Gurevych, Iryna AU - Stein, Benno ID - 20188 T2 - Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies TI - The Argument Reasoning Comprehension Task: Identification and Reconstruction of Implicit Warrants ER - TY - CONF AU - Al Khatib, Khalid AU - Wachsmuth, Henning AU - Lang, Kevin AU - Herpel, Jakob AU - Hagen, Matthias AU - Stein, Benno ID - 3804 T2 - Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) TI - Modeling Deliberative Argumentation Strategies on Wikipedia ER - TY - CONF AU - Habernal, Ivan AU - Wachsmuth, Henning AU - Gurevych, Iryna AU - Stein, Benno ID - 3806 T2 - Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) TI - Before Name-Calling: Dynamics and Triggers of Ad Hominem Fallacies in Web Argumentation ER - TY - CONF AU - Habernal, Ivan AU - Wachsmuth, Henning AU - Gurevych, Iryna AU - Stein, Benno ID - 3807 T2 - Proceedings of The 12th International Workshop on Semantic Evaluation TI - SemEval-2018 Task 12: The Argument Reasoning Comprehension Task ER - TY - CONF AU - Wachsmuth, Henning AU - Syed, Shahbaz AU - Stein, Benno ID - 3821 T2 - Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) TI - Retrieval of the Best Counterargument without Prior Topic Knowledge ER - TY - CONF AU - Wachsmuth, Henning AU - Stede, Manfred AU - El Baff, Roxanne AU - Al Khatib, Khalid AU - Skeppstedt, Maria AU - Stein, Benno ID - 4236 KW - argument T2 - Proceedings of the 27th International Conference on Computational Linguistics TI - Argumentation Synthesis following Rhetorical Strategies ER - TY - CONF AU - Ajjour, Yamen AU - Wachsmuth, Henning AU - Kiesel, Dora AU - Riehmann, Patrick AU - Fan, Fan AU - Castiglia, Giuliano AU - Adejoh, Rosemary AU - Fröhlich, Bernd AU - Stein, Benno ID - 11711 T2 - Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations TI - Visualization of the Topic Space of Argument Search Results in args. me ER - TY - CONF AU - El Baff, Roxanne AU - Wachsmuth, Henning AU - Al Khatib, Khalid AU - Stein, Benno ID - 11712 T2 - Proceedings of the 22nd Conference on Computational Natural Language Learning TI - Challenge or Empower: Revisiting Argumentation Quality in a News Editorial Corpus ER - TY - JOUR AU - Chen, Wei-Fan AU - Ku, Lun-Wei ID - 14886 IS - 10 JF - IEEE Transactions on Knowledge and Data Engineering TI - We Like, We Post: A Joint User-Post Approach for Facebook Post Stance Labeling VL - 30 ER - TY - JOUR AU - Chen, Mei-Hua AU - Chen, Wei-Fan AU - Ku, Lun-Wei ID - 14887 JF - IEEE Access TI - Application of Sentiment Analysis to Language Learning VL - 6 ER - TY - JOUR AU - Chen, Wei-Fan AU - Ku, Lun-Wei ID - 14888 JF - 圖書館學與資訊科學 TI - 中文情感語意分析套件 CSentiPackage 發展與應用 ER - TY - JOUR AU - Kiesel, Johannes AU - Kneist, Florian AU - Alshomary, Milad AU - Stein, Benno AU - Hagen, Matthias AU - Potthast, Martin ID - 10331 JF - Journal of Data and Information Quality SN - 1936-1955 TI - Reproducible Web Corpora ER - TY - CONF AU - Chen, Wei-Fan AU - Wachsmuth, Henning AU - Al Khatib, Khalid AU - Stein, Benno ID - 11710 T2 - Proceedings of the 11th International Conference on Natural Language Generation TI - Learning to Flip the Bias of News Headlines ER - TY - CONF AU - Chen, Wei-Fan AU - Hagen, Matthias AU - Stein, Benno AU - Potthast, Martin ID - 14873 T2 - Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval TI - A User Study on Snippet Generation: Text Reuse vs. Paraphrases ER - TY - CONF AU - Potthast, Martin AU - Chen, Wei-Fan AU - Hagen, Matthias AU - Stein, Benno ID - 14885 T2 - Proceedings of the Second International Workshop on Recent Trends in News Information Retrieval TI - A Plan for Ancillary Copyright: Original Snippets. ER - TY - CONF AU - Ajjour, Yamen AU - Chen, Wei-Fan AU - Kiesel, Johannes AU - Wachsmuth, Henning AU - Stein, Benno ID - 3751 T2 - Proceedings of the 4th Workshop on Argument Mining TI - Unit Segmentation of Argumentative Texts ER - TY - CONF AU - Al Khatib, Khalid AU - Wachsmuth, Henning AU - Hagen, Matthias AU - Stein, Benno ID - 3803 T2 - Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing TI - Patterns of Argumentation Strategies across Topics ER - TY - CONF AU - Kiesel, Johannes AU - Wachsmuth, Henning AU - Al Khatib, Khalid AU - Stein, Benno ID - 3809 T2 - Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics TI - WAT-SL: A Customizable Web Annotation Tool for Segment Labeling ER - TY - CONF AU - Wachsmuth, Henning AU - Stein, Benno AU - Ajjour, Yamen ID - 3817 T2 - Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers TI - "Page Rank'' for Argument Relevance ER - TY - CONF AU - Wachsmuth, Henning AU - Potthast, Martin AU - Al-Khatib, Khalid AU - Ajjour, Yamen AU - Puschmann, Jana AU - Qu, Jiani AU - Dorsch, Jonas AU - Morari, Viorel AU - Bevendorff, Janek AU - Stein, Benno ID - 3819 T2 - Proceedings of the 4th Workshop on Argument Mining TI - Building an Argument Search Engine for the Web ER - TY - CONF AU - Wachsmuth, Henning AU - Da San Martino, Giovanni AU - Kiesel, Dora AU - Stein, Benno ID - 3820 T2 - Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing TI - The Impact of Modeling Overall Argumentation with Tree Kernels ER - TY - CONF AU - Wachsmuth, Henning AU - Naderi, Nona AU - Hou, Yufang AU - Bilu, Yonatan AU - Prabhakaran, Vinodkumar AU - Thijm, Tim Alberdingk AU - Hirst, Graeme AU - Stein, Benno ID - 3881 T2 - Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers TI - Computational Argumentation Quality Assessment in Natural Language ER - TY - JOUR AU - Wachsmuth, Henning AU - Stein, Benno ID - 3882 IS - 3 JF - Special Section of the ACM Transactions on Internet Technology: Argumentation in Social Media SN - 1533-5399 TI - A Universal Model for Discourse-Level Argumentation Analysis ER - TY - CONF AU - Wachsmuth, Henning AU - Naderi, Nona AU - Habernal, Ivan AU - Hou, Yufang AU - Hirst, Graeme AU - Gurevych, Iryna AU - Stein, Benno ID - 3883 T2 - Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) TI - Argumentation Quality Assessment: Theory vs. Practice ER - TY - CONF AU - Hagen, Matthias AU - Kiesel, Johannes AU - Alshomary, Milad AU - Stein, Benno ID - 3904 T2 - Working Notes of CLEF 2017 - Conference and Labs of the Evaluation Forum TI - Webis at the CLEF 2017 Dynamic Search Lab ER - TY - CONF AU - Chen, Wei-Fan AU - Chen, Yi-Pei AU - Ku, Lun-Wei ID - 14884 T2 - International Conference on HCI in Business, Government, and Organizations TI - How to Get Endorsements? Predicting Facebook Likes Using Post Content and User Engagement ER - TY - CONF AU - Al Khatib, Khalid AU - Wachsmuth, Henning AU - Kiesel, Johannes AU - Hagen, Matthias AU - Stein, Benno ID - 3747 T2 - Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers TI - A News Editorial Corpus for Mining Argumentation Strategies ER - TY - CONF AU - Al-Khatib, Khalid AU - Wachsmuth, Henning AU - Hagen, Matthias AU - Köhler, Jonas AU - Stein, Benno ID - 3801 T2 - Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies TI - Cross-Domain Mining of Argumentative Text through Distant Supervision ER - TY - CONF AU - Wachsmuth, Henning AU - Al Khatib, Khalid AU - Stein, Benno ID - 3816 SN - 978-3-88579-975-7 T2 - Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers TI - Using Argument Mining to Assess the Argumentation Quality of Essays ER - TY - CONF AU - Wachsmuth, Henning ID - 3880 SN - 978-3-88579-975-7 T2 - Ausgezeichnete Informatikdissertationen 2015 TI - Pipelines Für Effiziente und Robuste Ad-hoc Textanalyse ER - TY - CONF AU - Chen, Wei-Fan AU - Ku, Lun-Wei ID - 14881 T2 - Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics TI - UTCNN: a Deep Learning Model of Stance Classification on Social Media Text ER - TY - CONF AU - Chen, Wei-Fan AU - Lin, Fang-Yu AU - Ku, Lun-Wei ID - 14882 T2 - Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations TI - WordForce: Visualizing Controversial Words in Debates ER - TY - GEN AU - Ku, Lun-Wei AU - Chen, Wei-Fan ID - 14883 T2 - Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Tutorial Abstracts TI - Chinese Textual Sentiment Analysis: Datasets, Resources and Tools ER - TY - CONF AU - Wachsmuth, Henning AU - Kiesel, Johannes AU - Stein, Benno ED - Tsujii, Junichi ED - Hajic, Jan ID - 3815 SN - 978-3-319-25740-2 T2 - Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing TI - Sentiment Flow - A General Model of Web Review Argumentation ER - TY - BOOK AU - Wachsmuth, Henning ID - 3879 SN - 978-3-319-25740-2 TI - Text Analysis Pipelines - Towards Ad-hoc Large-scale Text Mining ER - TY - THES AB - Today's web search and big data analytics applications aim to address information needs~(typically given in the form of search queries) ad-hoc on large numbers of texts. In order to directly return relevant information instead of only returning potentially relevant texts, these applications have begun to employ text mining. The term text mining covers tasks that deal with the inference of structured high-quality information from collections and streams of unstructured input texts. Text mining requires task-specific text analysis processes that may consist of several interdependent steps. These processes are realized with sequences of algorithms from information extraction, text classification, and natural language processing. However, the use of such text analysis pipelines is still restricted to addressing a few predefined information needs. We argue that the reasons behind are three-fold: First, text analysis pipelines are usually made manually in respect of the given information need and input texts, because their design requires expert knowledge about the algorithms to be employed. When information needs have to be addressed that are unknown beforehand, text mining hence cannot be performed ad-hoc. Second, text analysis pipelines tend to be inefficient in terms of run-time, because their execution often includes analyzing texts with computationally expensive algorithms. When information needs have to be addressed ad-hoc, text mining hence cannot be performed in the large. And third, text analysis pipelines tend not to robustly achieve high effectiveness on all texts, because their results are often inferred by algorithms that rely on domain-dependent features of texts. Hence, text mining currently cannot guarantee to infer high-quality information. In this thesis, we contribute to the question of how to address information needs from text mining ad-hoc in an efficient and domain-robust manner. We observe that knowledge about a text analysis process and information obtained within the process help to improve the design, the execution, and the results of the pipeline that realizes the process. To this end, we apply different techniques from classical and statistical artificial intelligence. In particular, we first develop knowledge-based approaches for an ad-hoc pipeline construction and for an optimal execution of a pipeline on its input. Then, we show theoretically and practically how to optimize and adapt the schedule of the algorithms in a pipeline based on information in the analyzed input texts in order to maximize execution efficiency. Finally, we learn patterns in the argumentation structures of texts statistically that remain strongly invariant across domains and that, thereby, allow for more robust analysis results in a restricted set of tasks. We formally analyze all developed approaches and we implement them as open-source software applications. Based on these applications, we evaluate the approaches on established and on newly created collections of texts for scientifically and industrially important text analysis tasks, such as financial event extraction and fine-grained sentiment analysis. Our findings show that text analysis pipelines can be designed automatically, which process only portions of text that are relevant for the information need at hand. Through scheduling, the run-time efficiency of pipelines can be improved by up to more than one order of magnitude while maintaining effectiveness. Moreover, we provide evidence that a pipeline's domain robustness substantially benefits from focusing on argumentation structure in tasks like sentiment analysis. We conclude that our approaches denote essential building blocks of enabling ad-hoc large-scale text mining in web search and big data analytics applications. AU - Wachsmuth, Henning ID - 7568 TI - Pipelines for Ad-hoc Large-scale Text Mining ER - TY - CONF AU - Chen, Wei-Fan AU - Chen, MeiHua AU - Ku, Lun-Wei ID - 14875 T2 - Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications TI - Embarrassed or Awkward? Ranking Emotion Synonyms for ESL Learners’ Appropriate Wording ER - TY - CONF AU - Chen, Wei-Fan AU - Ku, Lun-Wei AU - Lee, Yann-Hui ID - 14877 T2 - 2015 AAAI Spring Symposium Series TI - Mining Supportive and Unsupportive Evidence from Facebook Using Anti-reconstruction of the Nuclear Power Plant as an Example ER - TY - CONF AU - Chen, Wei-Fan AU - Lee, Yann-Hui AU - Ku, Lun-Wei ID - 14878 T2 - International Conference on HCI in Business TI - Topic-based Stance Mining for Social Media Texts ER - TY - JOUR AU - Chen, Wei-Fan AU - Chen, Mei-Hua AU - Chen, Ming-Lung AU - Ku, Lun-Wei ID - 14879 IS - 5 JF - IEEE Transactions on Knowledge and Data Engineering TI - A Computer-assistance Learning System for Emotional Wording VL - 28 ER - TY - CONF AU - Chen, Mei-Hua AU - Chen, Wei-Fan AU - Ku, Lun-Wei ID - 14876 T2 - Proceedings of the sixth joint Foreign Language Education and Technology Conference (FLEAT VI) TI - Technology Enhanced Emotion Expression Learning ER - TY - CONF AU - Wachsmuth, Henning AU - Trenkmann, Martin AU - Stein, Benno AU - Engels, Gregor AU - Palakarska, Tsvetomira ID - 20142 T2 - Proceedings of the 15th International Conference on Intelligent Text Processing and Computational Linguistics TI - A Review Corpus for Argumentation Analysis ER - TY - CONF AU - Brüseke, Frank AU - Wachsmuth, Henning AU - Engels, Gregor AU - Becker, Steffen ID - 3805 IS - 12 T2 - Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment TI - PBlaman: performance blame analysis based on Palladio contracts ER - TY - CONF AU - Wachsmuth, Henning AU - Trenkmann, Martin AU - Stein, Benno AU - Engels, Gregor ID - 3877 T2 - Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers TI - Modeling Review Argumentation for Robust Sentiment Analysis ER - TY - JOUR AU - Abu Quba Rana, Chamsi AU - Hassas, Salima AU - Usama, Fayyad AU - Alshomary, Milad AU - Gertosio, Christine ID - 3905 JF - 2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA) TI - iSoNTRE: The Social Network Transformer into Recommendation Engine ER - TY - CONF AU - Chen, Mei-Hua AU - Chen, Wei-Fan AU - Ku, Lun-Wei ID - 14874 T2 - Proceedings of the AsiaCALL 2014 TI - RESOLVE: An Emotion Word Suggestion System Facilitates Language Learners’ Emotional Expressions ER -