Fighting post-truth using natural language processing: A review and open challenges

2020
Post-truth is a term that describes a distorting phenomenon that aims to manipulate public opinion and behavior. One of its key engines is the spread of Fake News. Nowadays most news is rapidly disseminated in written language via digital media and social networks. Therefore, to detect fake news it is becoming increasingly necessary to apply Artificial Intelligence (Al) and, more specifically Natural Language Processing (NLP). This paper presents a review of the application of AI to the complex task of automatically detecting fake news. The review begins with a definition and classification of fake news. Considering the complexity of the fake news detection task, a divide-and-conquer methodology was applied to identify a series of subtasks to tackle the problem from a computational perspective. As a result, the following subtasks were identified: deception detection; stance detection; controversy and polarization; automated fact checking; clickbait detection; and, credibility scores. From each subtask, a PRISMA compliant systematic review of the main studies was undertaken, searching Google Scholar. The various approaches and technologies are surveyed, as well as the resources and competitions that have been involved in resolving the different subtasks. The review concludes with a roadmap for addressing the future challenges that have emerged from the analysis of the state of the art, providing a rich source of potential work for the research community going forward. (C) 2019 Elsevier Ltd. All rights reserved.
EXPERT SYSTEMS WITH APPLICATIONS
卷号:141
ISSN:0957-4174
来源机构
Universitat d'Alacant
收录类型
SSCI
发表日期
2020
学科领域
循证管理学
国家
西班牙
语种
英语
DOI
10.1016/j.eswa.2019.112943
其他关键词
SOCIAL MEDIA; PREDICTING DECEPTION; DETECTING DECEPTION; NEURAL-NETWORKS; CREDIBILITY; NEWS; INFORMATION; FACT; CUES; MOTIVATIONS
EISSN
1873-6793
资助机构
Generalitat Valenciana through project SIIA: Tecnologias del lenguaje humano para una sociedad inclusiva, igualitaria, y accesible [PROMETEU/2018/089]; Spanish GovernmentSpanish GovernmentEuropean Commission [RTI2018-094653-B-C22]; project Analisis de Sentimientos Aplicado a la Prevention del Suicidio en las Redes Sociales (ASAP) - Ayudas Fundacion BBVA a equipos de investigacion cientifica
资助信息
This research work has been partially funded by Generalitat Valenciana through project SIIA: Tecnologias del lenguaje humano para una sociedad inclusiva, igualitaria, y accesible with grant reference PROMETEU/2018/089, by the Spanish Government through project RTI2018-094653-B-C22: Modelado Del Comportamiento de Entidades Digitales Mediante Tecnologias Del Lenguaje Humano, as well as by the project Analisis de Sentimientos Aplicado a la Prevention del Suicidio en las Redes Sociales (ASAP) funded by Ayudas Fundacion BBVA a equipos de investigacion cientifica.
被引频次(WOS)
14
被引更新日期
2022-01
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