Research Area:  Machine Learning

Abstract:

Argument mining is the automatic identification and extraction of the structure of inference and reasoning expressed as arguments presented in natural language. Understanding argumentative structure makes it possible to determine not only what positions people are adopting, but also why they hold the opinions they do, providing valuable insights in domains as diverse as financial market prediction and public relations. This survey explores the techniques that establish the foundations for argument mining, provides a review of recent advances in argument mining techniques, and discusses the challenges faced in automatically extracting a deeper understanding of reasoning expressed in language in general.

Keywords:  

Author(s) Name:  John Lawrence, Chris Reed

Publisher name:  MIT Press

DOI:  10.1162/coli_a_00364

Volume Information:  Volume 45, Issue (4), Pages: 765–818.

Paper Link:   https://direct.mit.edu/coli/article/45/4/765/93362/Argument-Mining-A-Survey