Fake news, rumor, information pollution in social media and web: A contemporary survey of state-of-the-arts, challenges and opportunities

• Published in: Expert systems with applications Vol. 153; p. 112986
• Main Authors: Meel, Priyanka, Vishwakarma, Dinesh Kumar
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.09.2020; Elsevier BV
• Subjects: Clickbait; Containment; Decision making; Deep learning; Digital media; Fraudulent Content; Information dissemination; Information Pollution; Machine learning; Online Social Networks; Opinion Spam; Rumour Propagation; Social networks; Taxonomy; Deep learning; Rumour Propagation; Opinion Spam; Clickbait; Fraudulent Content; Machine learning; Information Pollution; Online Social Networks
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2019.112986

•A review of fake news, rumour, and information pollution are presented.•A statics of social media users and commercial analytics tools are outlined.•The popular social media platforms are identified and presented in a detailed form.•The state of online fact-checking tools and APIs are recognized and discussed.•The publicly available datasets are outlined along with experimental settings. Internet and social media have become a widespread, large scale and easy to use platform for real-time information dissemination. It has become an open stage for discussion, ideology expression, knowledge dissemination, emotions and sentiment sharing. This platform is gaining tremendous attraction and a huge user base from all sections and age groups of society. The matter of concern is that up to what extent the contents that are circulating among all these platforms every second changing the mindset, perceptions and lives of billions of people are verified, authenticated and up to the standards. This paper puts forward a holistic view of how the information is being weaponized to fulfil the malicious motives and forcefully making a biased user perception about a person, event or firm. Further, a taxonomy is provided for the classification of malicious information content at different stages and prevalent technologies to cope up with this issue form origin, propagation, detection and containment stages. We also put forward a research gap and possible future research directions so that the web information content could be more reliable and safer to use for decision making as well as for knowledge sharing.