---
_id: '48306'
abstract:
- lang: eng
  text: <jats:p>The goal of argumentation mining, an evolving research field in computational
    linguistics, is to design methods capable of analyzing people's argumentation.
    In this article, we go beyond the state of the art in several ways. (i) We deal
    with actual Web data and take up the challenges given by the variety of registers,
    multiple domains, and unrestricted noisy user-generated Web discourse. (ii) We
    bridge the gap between normative argumentation theories and argumentation phenomena
    encountered in actual data by adapting an argumentation model tested in an extensive
    annotation study. (iii) We create a new gold standard corpus (90k tokens in 340
    documents) and experiment with several machine learning methods to identify argument
    components. We offer the data, source codes, and annotation guidelines to the
    community under free licenses. Our findings show that argumentation mining in
    user-generated Web discourse is a feasible but challenging task.</jats:p>
author:
- first_name: Ivan
  full_name: Habernal, Ivan
  id: '101881'
  last_name: Habernal
- first_name: Iryna
  full_name: Gurevych, Iryna
  last_name: Gurevych
citation:
  ama: Habernal I, Gurevych I. Argumentation Mining in User-Generated Web Discourse.
    <i>Computational Linguistics</i>. 2016;43(1):125-179. doi:<a href="https://doi.org/10.1162/coli_a_00276">10.1162/coli_a_00276</a>
  apa: Habernal, I., &#38; Gurevych, I. (2016). Argumentation Mining in User-Generated
    Web Discourse. <i>Computational Linguistics</i>, <i>43</i>(1), 125–179. <a href="https://doi.org/10.1162/coli_a_00276">https://doi.org/10.1162/coli_a_00276</a>
  bibtex: '@article{Habernal_Gurevych_2016, title={Argumentation Mining in User-Generated
    Web Discourse}, volume={43}, DOI={<a href="https://doi.org/10.1162/coli_a_00276">10.1162/coli_a_00276</a>},
    number={1}, journal={Computational Linguistics}, publisher={MIT Press}, author={Habernal,
    Ivan and Gurevych, Iryna}, year={2016}, pages={125–179} }'
  chicago: 'Habernal, Ivan, and Iryna Gurevych. “Argumentation Mining in User-Generated
    Web Discourse.” <i>Computational Linguistics</i> 43, no. 1 (2016): 125–79. <a
    href="https://doi.org/10.1162/coli_a_00276">https://doi.org/10.1162/coli_a_00276</a>.'
  ieee: 'I. Habernal and I. Gurevych, “Argumentation Mining in User-Generated Web
    Discourse,” <i>Computational Linguistics</i>, vol. 43, no. 1, pp. 125–179, 2016,
    doi: <a href="https://doi.org/10.1162/coli_a_00276">10.1162/coli_a_00276</a>.'
  mla: Habernal, Ivan, and Iryna Gurevych. “Argumentation Mining in User-Generated
    Web Discourse.” <i>Computational Linguistics</i>, vol. 43, no. 1, MIT Press, 2016,
    pp. 125–79, doi:<a href="https://doi.org/10.1162/coli_a_00276">10.1162/coli_a_00276</a>.
  short: I. Habernal, I. Gurevych, Computational Linguistics 43 (2016) 125–179.
date_created: 2023-10-19T08:30:44Z
date_updated: 2023-10-19T12:08:00Z
department:
- _id: '34'
- _id: '820'
doi: 10.1162/coli_a_00276
intvolume: '        43'
issue: '1'
keyword:
- Artificial Intelligence
- Computer Science Applications
- Linguistics and Language
- Language and Linguistics
language:
- iso: eng
page: 125-179
publication: Computational Linguistics
publication_identifier:
  issn:
  - 0891-2017
  - 1530-9312
publication_status: published
publisher: MIT Press
status: public
title: Argumentation Mining in User-Generated Web Discourse
type: journal_article
user_id: '15504'
volume: 43
year: '2016'
...