We would like to invite you to participate in The 8th Workshop on Argument Mining (ArgMining21), held in conjunction with EMNLP 2021 November 10-11, 2021.
**Introduction**
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.
**Topics of interest**
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.
**Submissions**
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.
Submission URL: https://www.softconf.com/emnlp2021/ArgMining/
**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