Stance detection on social media: State of the art and trends

作者：

Highlights：

• We map out the current research terrain on stance detection and synthesize its relation to the existing theoretical orientations.

• We provide a broader overview of stance detection methods, covering work that has been published in multiple research domains, including NLP, Computational Social Science,and Web science.

• We survey the recent advances in stance detection methodologies and potential benchmarks by categorizing and summarizing the current methods.

• We show the different applications of stance detection on social media and identify open key trends and challenges in the domain.

摘要

•We map out the current research terrain on stance detection and synthesize its relation to the existing theoretical orientations.•We provide a broader overview of stance detection methods, covering work that has been published in multiple research domains, including NLP, Computational Social Science,and Web science.•We survey the recent advances in stance detection methodologies and potential benchmarks by categorizing and summarizing the current methods.•We show the different applications of stance detection on social media and identify open key trends and challenges in the domain.

论文关键词：00-01,99-00,Stance detection,Stance,Social media,Stance classification

论文评审过程：Received 25 November 2020, Revised 16 March 2021, Accepted 20 March 2021, Available online 13 April 2021, Version of Record 13 April 2021.

论文官网地址：https://doi.org/10.1016/j.ipm.2021.102597