Argumentation Mining. By Manfred Stede and Jodi Schneider (University of Potsdam, University of Illinois at Urbana-Champaign). Morgan & Claypool (Synthesis Lectures on Human Language Technologies, edited by Graeme Hirst, volume 40), 2018, xvi+175 pp; paperback, ISBN 978-1-68173-459-0; ebook, ISBN 978-1-68173-460-6; doi:10.2200/S00883ED1V01Y201811HLT040

Argumentation is pervasive—in everyday life as well as in politics and media. People exchange arguments to persuade each other, to achieve agreement, to make decisions, and more. Argumentation has been studied since ancient times (Aristotle 2007), and it is an active research topic across disciplines today, from logic to rhetoric to linguistics (van Eemeren et al. 2014). In a time of alternative facts and filter bubbles, arguments are of ever-increasing importance; when the truth of facts is unclear, we need to compare reasons for opposing claims, and we should do so beyond our own view. Computational research on argumentation is still young. It first evolved in the AI community, oriented towards formal argumentation (Dung 1995). Except for some early pioneering works, the natural language side is getting attention since the publication of the first approaches to mine arguments from text (Palau and Moens 2009). Since then, computational linguistics research on argumentation grows constantly, and impressive industrial applications such as IBM’s Debater start to appear. Since 2014, the ArgMining workshop series exists, annually taking place at ACL, EMNLP, or NAACL. Wachsmuth, Henning. 2019. Book Reviews. Computational Linguistics, uncorrected proof.