First Call for Papers (apologies for cross-posting)
Argument mining (also known as "argumentation mining") is a growing 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 pro- and con-relations. To date, researchers have investigated argument mining on many genres, such as legal documents, product reviews, news articles, online debates, Wikipedia articles, essays, academic literature, tweets, and dialogues. In addition, argument quality assessment and generation are also important problems. 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 written text and dialogue and that enable argument search on the web for a topic of interest. In educational contexts, argument mining can be applied to written and diagrammed arguments for instructing and assessing students' critical thinking. In information retrieval, argument mining is expected to play a salient role in the emerging field of conversational search.
SURVEY ON WORKSHOP FORMAT If you are interested in the workshop, please fill in our survey https://docs.google.com/forms/d/1o5MzkSI9CeP_dcFKHqYNT_RwY_G-jwkZm1Hy9snyMpk/edit Knowing your preferences will help us find the right format and make it engaging and useful!
CALL FOR PAPERS ArgMining 2022 invites the submission of long and short papers on substantial, original, and unpublished research in all aspects of argument mining.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 (premises and conclusions or more fine-grained), and relations between arguments and counterarguments (support and attack or more fine-grained) within/across documents
• Automatic assessment of properties of arguments and argumentation, such as argumentation schemes, stance, quality, and persuasiveness
• Automatic synthesis of arguments and their components, including the consideration of discourse goals (e.g., stages of a critical discussion or rhetorical strategies) and the possibly needed preceding analyses
• Creation and evaluation of argument annotation schemes, relationships to linguistic and discourse annotations, (semi-) automatic argument annotation methods and tools, and creation of argumentation corpora
• Management of spoken and transcribed dialogue, argument mining from such data, including additional challenges posed by real-time processing
• Combination of NLP methods and AI models developed for argumentation, such as abstract and structured argumentation frameworks
• Combination of information retrieval methods with argument mining, e.g. in order to build the next generation of argumentative (web) search engines
• Use of argument mining for studying research questions from the social sciences, digital humanities, and related fields
• Reflection on the ethical aspects and societal impact of argument mining methods
Special theme: Argument Mining in Real-World Applications Commonly explored real-world applications include argument web search, opinion analysis in customer reviews, argument analysis in meetings, scientific writing. In addition to such well known applications, we are particularly interested in cross-disciplinary use-cases targeting domains such education, political and social science, and the legal domain.
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 COLING 2022 style sheets for formatting your paper: https://coling2022.org/ Submission URL (softconf): to be announced
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.
• Submission due: July 11, 2022
• Notification of acceptance: August 22, 2021
• Camera-ready papers due: September 5, 2022
• Workshop: TBD: COLING 2022 October 12-17, 2022 All deadlines are 11.59 pm UTC -12h (“anywhere on Earth”).
SHARED TASK: WE ARE LOOKING FOR PROPOSALS! If you have ideas for a shared task, send them by email to argmining.org at gmail.com We are not calling for formal proposals: just give us an idea of what the task would be, who would be involved, and whether you already have data and worked with it. We encourage you to mention publications on the task/data you are proposing! We expect to make a decision concerning the shared task at the end of April, so proposals which reach us until then will receive full consideration.
ORGANIZERS Gabriella Lapesa (University of Stuttgart) Jodi Schneider (University of Illinois) Yohan Jo (Amazon) Sougata Saha (University at Buffalo, New York)