Argumentation Mining in User-Generated Web Discourse

Argumentation Mining in User-Generated Web Discourse Ivan Habernal∗ German Institute for Educational Research and Technische Universit¨at Darmstadt Iryna Gurevych∗∗ Technische Universit¨at Darmstadt and German Institute for Educational Research 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 exten- sive 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. 1. Introduction The art of argumentation has been studied since the early work of Aristotle, dating back to the 4th century BCE (Aristotle and Kennedy [translator] 1991). It has been exhaustively examined from different perspectives, such as philosophy, psychology, ∗ Ubiquitous Knowledge Processing Lab (UKP-DIPF), German Institute for Educational Research, Schloßstraße 29, D-60486 Frankfurt am Main, Germany and Technische Universit¨at Darmstadt, Ubiquitous Knowledge Processing (UKP) Lab, TU Darmstadt - FB 20a Hochschulstrasse 10, D-64289 Darmstadt, Germany. E-mail: habernal@ukp.informatik.tu-darmstadt.de ∗∗ Technische Universit¨at Darmstadt, Ubiquitous Knowledge Processing (UKP) Lab, TU Darmstadt - FB 20a Hochschulstrasse 10, D-64289 Darmstadt, Germany and Ubiquitous Knowledge Processing Lab (UKP-DIPF), German Institute for Educational Research, Schloßstraße 29, D-60486 Frankfurt am Main, Germany. Submission received: 2 April 2015; revised version received: 20 April 2016; accepted for publication: 14 June 2016. doi:10.1162/COLI a 00276 © 2017 Association for Computational Linguistics Published under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license Computational Linguistics Volume 43, Number 1 communication studies, cognitive science, formal and informal logic, linguistics, com- puter science, educational research, and many others. In a recent and critically well- acclaimed study, Mercier and Sperber (2011) even claim that argumentation is what drives humans to perform reasoning. From the pragmatic perspective, argumenta- tion can be seen as a verbal activity oriented towards the realization of a goal (Micheli 2011) or more in detail as a verbal, social, and rational activity aimed at convincing a reasonable critic of the acceptability of a standpoint by putting forward a constellation of one or more propositions to justify this standpoint (van Eemeren, Grootendorst, and Snoeck Henkemans 2002). Analyzing argumentation from the computational linguistics point of view has very recently led to a new field called argumentation mining (Green et al. 2014). Despite the lack of an exact definition, researchers within this field usually focus on analyzing discourse on the pragmatics level and applying a certain argumentation theory to model and analyze textual data1 at hand. Our motivation for argumentation mining …

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