Computational Models of Argument : Proceedings of COMMA 2016

Argument Analytics

Rapid growth in the area of argument mining has resulted in an ever increasing volume of analysed argument data. Being able to store information about arguments people make in favour or against different opinions, decisions and actions is a highly valuable resource, yet extremely challenging for sense-making. How, for example, can an analyst quickly check whether in a corpus of citizen dialogue people tend to rather agree or disagree with new policies proposed by the department of transportation; how can she get an insight into the interactions typical of this specific dialogical context; how can the general public easily see which presidential candidate is currently winning the debate by being able to successfully defend his arguments? In this paper, we propose Argument Analytics – a suite of techniques which provide interpretation of, and insight into, large-scale argument data for both specialist and general audiences.

Lawrence, J.; Duthie, R.; Budzynska, K. and Reed, C. (2016). Argument Analytics. In Computational Models of Argument : Proceedings of COMMA 2016 (Frontiers in artificial intelligence and applications ; v. 287) 371 - 378. doi: 10.3233/978-1-61499-686-6-371