Fighting post-truth using natural language processing: A review and open challenges
作者：
Highlights：
• The study describes the problem of fake news phenomena in digital information.
• The study provides a systematic review of the state-of-the-art regarding automatic fake news detection.
• From the review, the main subtasks involved in automatic fake news detection are detected and classified.
• The review covers systems, resources and competitions in automatic fake news detection.
• The review outlines knowledge gaps and future challenges related to automatic fake news detection.
摘要
•The study describes the problem of fake news phenomena in digital information.•The study provides a systematic review of the state-of-the-art regarding automatic fake news detection.•From the review, the main subtasks involved in automatic fake news detection are detected and classified.•The review covers systems, resources and competitions in automatic fake news detection.•The review outlines knowledge gaps and future challenges related to automatic fake news detection.
论文关键词：Natural language processing,Fake news,Post-truth,Deception detection,Automatic fact-checking,Clickbait detection,Stance detection,Credibility,Human language technologies,Applied computing,Document management and text processing,Document capture,Document analysis
论文评审过程：Received 1 May 2019, Revised 24 July 2019, Accepted 7 September 2019, Available online 9 September 2019, Version of Record 18 September 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.112943
