ArgMining 2021
The 8th Workshop on Argument Mining, 2021
co-located with EMNLP 2021, in Punta Cana, Dominican Republic

Argument mining (also known as “argumentation mining”) is a young and gradually maturing research area within computational linguistics. At its heart, argument mining involves the automatic identification of argumentative structures in free text, such as the conclusions, premises, and inference schemes of arguments as well as their interrelations and counter-considerations. To date, researchers have investigated argument mining on genres such as legal documents, product reviews, news articles, online debates, user-generated web discourse, Wikipedia articles, academic literature, persuasive essays, tweets, and dialogues. Recently, also argument quality assessment and generation came into focus. In addition, argument mining is inherently tied to stance and sentiment analysis, since every argument carries a stance towards its topic, often expressed with sentiment.

Argument mining gives rise to various practical applications of great importance. In particular, it provides methods that can find and visualize the main pro and con arguments in a text corpus — or even on in an argument search on the web — towards a topic or query of interest. In instructional contexts, written and diagrammed arguments represent educational data that can be mined for conveying and assessing students’ command of course material. In information retrieval, argument mining is expected to play a salient role in the emerging field of conversational search. And with the IBM Debater Project, technology based on argument mining recently received a lot of media attention.

While solutions to basic tasks such as component segmentation and classification slowly become mature, many tasks remain largely unsolved, particularly in more open genres and topical domains. Success in argument mining requires interdisciplinary approaches informed by NLP technology, theories of semantics, pragmatics and discourse, knowledge of discourse in application domains, artificial intelligence, information retrieval, argumentation theory, and computational models of argumentation.

Call for Papers

ArgMining 2021 invites the submission of long and short papers on substantial, original, and unpublished research in all aspects of argument mining. The workshop solicits LONG and SHORT papers for oral and poster presentations, as well as DEMOS of argument/argumentation mining systems and tools.

The topics for submissions include but are not limited to:
  • Automatic identification of argument components (e.g., premises and conclusions), and relations between arguments (e.g., support and attack) in as well as across documents
  • Automatic assessment of properties of arguments and argumentation, such as argumentation schemes, stance, quality, and persuasiveness
  • Creation and evaluation of argument annotation schemes, developing automatic and semi-automatic argument annotation methods and tools, and building high-quality annotated datasets, benchmarks, and Knowledge graphs
  • Automatic retrieval, summarization, and generation of arguments
  • Applications of argument mining and computational argumentation to various domains and data such as social sciences and humanities texts, legal and technical documents, scientific papers, news corpora, Wikipedia articles, consumer reviews, user-generated content, and students’ written essays.

This year, the workshop plans to have a joint session with the workshop CODI (Computational Approaches to Discourse). Submissions that address argumentation from an angle that overlaps with discourse structure phenomena will be considered for that session. (Authors may but need not make this potential overlap explicit)

Submission Information

Three types of papers can be submitted: Long papers (8 pages + references), short papers (4 pages + references), and demo papers (4 pages + references). Demo papers must include a URL to a running demo. Accepted papers will be given an additional page to account for the reviewers' comments. All papers will be treated equally in the workshop proceedings. The workshop follows ACL’s policies for submission, review, and citation. Moreover, authors are expected to adhere to the ethical code set out in the ACL Code of Ethics. Submissions that violate any of the policies will be rejected without review.

Please use the EMNLP 2021 style sheets for formatting your paper:
Submission URL:

The workshop is running a double-blind review process. In preparing your manuscript, do not include any information which could reveal your identity, or that of your co-authors. The title section of your manuscript should not contain any author names, email addresses, or affiliation status. If you do include any author names on the title page, your submission will be automatically rejected. In the body of your submission, you should eliminate all direct references to your own previous work. That is, avoid phrases such as "this contribution generalizes our results for XYZ". Also, please do not disproportionately cite your own previous work. In other words, make your submission as anonymous as possible. We need your cooperation in our effort to maintain a fair, double-blind reviewing process - and to consider all submissions equally. Double Submission Papers that have been or will be submitted to other venues should indicate this at submission time. Upon acceptance at either event, the submission must be withdrawn from the other. To save reviewers' efforts, avoid submitting (or withdraw early) papers that are on track to be accepted elsewhere.

Shared Tasks

ArgMining 2021 includes the following shared tasks:

  1. Quantitative Summarization – Key Point Analysis

For detailed information about the tasks, data, evaluation, and organisers, please see the shared tasks page.

Important Dates

  • Submission due: August 20, 2021 **Extended Deadline**
  • Notification of acceptance: September 15, 2021
  • Camera-ready papers due: September 23, 2021
  • Workshop: November 10-11, 2021
All deadlines are 11.59 pm UTC -12h (“anywhere on Earth”).


November 10, 2021
09:00 – 09:30 Opening Remarks
09:30 – 10:30 Invited Talk 1
10:30 – 11:00 Coffee Break
11:00–12:00 Session 1
11:00 – 11:20 long Argument Mining on Twitter: A Case Study on the Planned Parenthood Debate
Muhammad Mahad Afzal Bhatti, Ahsan Suheer Ahmad and Joonsuk Park
11:20 – 11:40 long Multi-task and Multi-corpora Training Strategies to Enhance Argumentative Sentence Linking Performance
Jan Wira Gotama Putra, Simone Teufel and Takenobu Tokunaga
11:40 – 12:00 long Explainable Unsupervised Argument Similarity Rating with Abstract Meaning Representation and Conclusion Generation
Juri Opitz, Philipp Heinisch, Philipp Wiesenbach, Philipp Cimiano and Anette Frank
12:00 – 13:00 Lunch Break
13:00 – 16:45 Session 2
13:00 – 13:20 finding Knowledge-Enhanced Evidence Retrieval for Counterargument Generation
Yohan Jo, Haneul Yoo, JinYeong Bak, Alice Oh, Chris Reed and Eduard Hovy
13:20 – 13:40 finding On Classifying whether Two Texts are on the Same Side of an Argument
Erik Körner, Gregor Wiedemann, Ahmad Hakimi, Gerhard Heyer and Martin Potthast
13:40 – 13:52 short Multilingual Counter Narrative Type Classification
Yi-Ling Chung, Marco Guerini and Rodrigo Agerri
13:52 – 13:64 short Predicting Moderation of Deliberative Arguments: Is Argument Quality the Key?
Neele Falk, Iman Jundi, Eva Maria Vecchi and Gabriella Lapesa
14:04 – 14:16 short Self-trained Pretrained Language Models for Evidence Detection
Mohamed Elaraby and Diane Litman
14:16 – 14:28 short Multi-task Learning in Argument Mining for Persuasive Online Discussions
Nhat Tran and Diane Litman
14:30 – 14:45 Coffee Break
14:45 – 16:15 Panel Talks and Discussion
16:15 – 16:45 Coffee Break
16:45–17:45 Session 3
16:45 – 17:05 long Image Retrieval for Arguments Using Stance-Aware Query Expansion
Johannes Kiesel, Nico Reichenbach, Benno Stein and Martin Potthast
17:05 – 17:25 long Is Stance Detection Topic-Independent and Cross-topic Generalizable? - A Reproduction Study
Myrthe Reuver, Suzan Verberne, Roser Morante and Antske Fokkens
17:25 – 17:45 long Exploring Methodologies for Collecting High-Quality Implicit Reasoning in Arguments
Keshav Singh, Farjana Sultana Mim, Naoya Inoue, Shoichi Naito and Kentaro Inui
November 11, 2021
09:00 – 10:00 Invited Talk 2
10:00–11:00 Session 4
10:00 – 10:20 long Assessing the Sufficiency of Arguments through Conclusion Generation
Timon Gurcke, Milad Alshomary and Henning Wachsmuth
10:20 – 10:40 long M-Arg: Multimodal Argument Mining Dataset for Political Debates with Audio and Transcripts
Rafael Mestre, Razvan Milicin, Stuart E. Middleton, Matt Ryan, Jiatong Zhu and Timothy J. Norman
10:40 – 11:00 Coffee Break
11:00–12:00 Session 5
11:00 – 11:20 long Citizen Involvement in Urban Planning - How Can Municipalities Be Supported in Evaluating Public Participation Processes for Mobility Transitions?
Julia Romberg and Stefan Conrad
11:20 – 11:40 long Argumentation Mining in Scientific Literature for Sustainable Development
Aris Fergadis, Dimitris Pappas, Antonia Karamolegkou and Haris Papageorgiou
11:40 – 12:00 long Bayesian Argumentation-Scheme Networks: A Probabilistic Model of Argument Validity Facilitated by Argumentation Schemes
Takahiro Kondo, Koki Washio, Katsuhiko Hayashi and Yusuke Miyao
12:00 – 13:00 Lunch Break
13:00 – 14:30 Shared Task Presentation
14:30 – 14:45 Break
14:45 – 15:00 Concluding Remarks

* The schedule is based on the Atlantic Standard Time (Punta Cana, Dominican Republic (GMT-4)).


Organizing Committee

Khalid Al-Khatib Leipzig University
Yufang Hou
Yufang Hou IBM Research, Dublin, Ireland
Manfred Stede
Manfred Stede Potsdam University, Germany

Program Committee

  • Stergos D. Afantenos, Université Paul Sabatier
  • Milad Alshomary, Paderborn University
  • Kevin Ashley, University of Pittsburgh
  • Roy Bar-Haim, IBM Research AI
  • Miriam Butt, University of Konstanz
  • Elena Cabrio, CNRS, Inria, I3S
  • Shohreh Haddadan, University of Luxembourg
  • Christopher Hidey, Google
  • Xinyu Hua, Bloomberg LP
  • Yohan Jo, Amazon
  • Christopher Klamm, Technische Universitat Darmstadt
  • Gabriella Lapesa, University of Stuttgart
  • Anne Lauscher, University of Mannheim
  • John Lawrence, University of Dundee
  • Diane Litman, University of Pittsburgh
  • Elena Musi, Columbia University
  • Alexis Palmer, University of Colorado
  • Joonsuk Park, University of Richmond
  • Simon Parsons, King's College London
  • Georgios Petasis, NCSR Demokritos
  • Olesya Razuvayevskaya, European Bioinformatics Institute
  • Chris Reed, University of Dundee
  • Patrick Saint-Dizier, IRIT - CNRS
  • Jodi Schneider, University of Illinois at Urbana Champaign
  • Benno Stein, Bauhaus-Universitat Weimar
  • Shahbaz Syed, Leipzig University
  • Nicolas Turenne, UMR LISIS (INRA,UPEM,CNRS)
  • Serena Villata, CNRS
  • Henning Wachsmuth, Paderborn University
  • Vern R. Walker, Maurice A. Hofstra University
  • Zhongyu Wei, Fudan University
  • Magdalena Wolska, Bauhaus-Universitat Weimar

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