Fake News Types and Detection Models on Social Media A State-of-the-Art Survey

Fake news has gained prominence since the 2016 US presidential election as well as the Brexit referendum. Fake news has abused not only the press but also the democratic rules. Therefore, the need to restrict and eliminate it becomes inevitable. The popularity of fake news on social media has made people unwilling to engage in sharing positive news for fear that the information is false. The main problem with fake news is how quickly it spreads to social media.

[1]  Ngoc Thanh Nguyen,et al.  Multi-step Consensus: An Effective Approach for Determining Consensus in Large Collectives , 2019, Cybern. Syst..

[2]  Massimo Di Pierro,et al.  Automatic Online Fake News Detection Combining Content and Social Signals , 2018, 2018 22nd Conference of Open Innovations Association (FRUCT).

[3]  V. S. Subrahmanian,et al.  Using sentiment to detect bots on Twitter: Are humans more opinionated than bots? , 2014, 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014).

[4]  Reza Zafarani,et al.  Fake News: Fundamental Theories, Detection Strategies and Challenges , 2019, WSDM.

[5]  Jon Roozenbeek,et al.  Fake news game confers psychological resistance against online misinformation , 2019, Palgrave Communications.

[6]  Maria Sokhn,et al.  Hybrid Machine-Crowd Approach for Fake News Detection , 2018, 2018 IEEE 4th International Conference on Collaboration and Internet Computing (CIC).

[7]  Nir Kshetri,et al.  The Economics of “Fake News” , 2017, IT Professional.

[8]  Miki Tanikawa,et al.  What Is News? What Is the Newspaper? The Physical, Functional, and Stylistic Transformation of Print Newspapers, 1988–2013 , 2017 .

[9]  Victoria L. Rubin,et al.  Challenges in automated deception detection in computer-mediated communication , 2011, ASIST.

[10]  Yimin Chen,et al.  Deception detection for news: Three types of fakes , 2015, ASIST.

[11]  David G. Rand,et al.  Fighting misinformation on social media using crowdsourced judgments of news source quality , 2018, Proceedings of the National Academy of Sciences.

[12]  Edson C. Tandoc,et al.  Defining “Fake News” , 2018 .

[13]  Huan Liu,et al.  Detecting Fake News on Social Media , 2019, Synthesis Lectures on Data Mining and Knowledge Discovery.

[14]  Prakhar Biyani,et al.  "8 Amazing Secrets for Getting More Clicks": Detecting Clickbaits in News Streams Using Article Informality , 2016, AAAI.

[15]  Marcus Messner,et al.  Read All About It: The Politicization of “Fake News” on Twitter , 2018 .

[16]  Miriam J. Metzger,et al.  The science of fake news , 2018, Science.

[17]  Sucipto Sucipto,et al.  Hoax Detection at Social Media With Text Mining Clarification System-Based , 2018 .

[18]  Vitaly Klyuev,et al.  Fake News Filtering: Semantic Approaches , 2018, 2018 7th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO).

[19]  Mykhailo Granik,et al.  Fake news detection using naive Bayes classifier , 2017, 2017 IEEE First Ukraine Conference on Electrical and Computer Engineering (UKRCON).

[20]  H. Gans Deciding What's News: A Study of CBS Evening News, NBC Nightly News, Newsweek and Time , 1979 .

[21]  Alfredo Cuzzocrea,et al.  Fighting fake news spread in online social networks: Actual trends and future research directions , 2017, 2017 IEEE International Conference on Big Data (Big Data).

[22]  William Yang Wang “Liar, Liar Pants on Fire”: A New Benchmark Dataset for Fake News Detection , 2017, ACL.