Argument Mining: A Survey

John Lawrence (Lead / Corresponding author), Chris Reed

Research output: Contribution to journalArticlepeer-review

111 Citations (Scopus)
306 Downloads (Pure)


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.

Original languageEnglish
Pages (from-to)765-818
Number of pages54
JournalComputational Linguistics
Issue number4
Publication statusPublished - 1 Jan 2020


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