Disentangling the Thoughts: Latest News in Computational Argumentation

In this talk, I will present a bunch of papers on argument mining (co-)authored by the UKP Lab in Darmstadt. The papers have appeared in NAACL, TACL and related venues in 2018. In the first part, I will talk about large-scale argument search, classification and reasoning. In the second part, the focus will be on mitigating high annotation costs for argument annotation. Specifically, we tackle small-data scenarios for novel argument tasks, less-resourced languages or web-scale argument analysis tasks such as detecting fallacies. The talk presents the results of ongoing projects in Computational Argumentation at the Technische Universität Darmstadt [1]: Argumentation Analysis for the Web (ArguAna) [2], Decision Support by Means of Automatically Extracting Natural Language Arguments from Big Data (ArgumenText) [3].[1] https://www.ukp.tu-darmstadt.de/research/research-areas/argumentation-mining/[2] https://www.informatik.tu-darmstadt.de/ukp/research_6/current_projects/arguana/index.en.jsp[3] https://www.argumentext.de