Automatic deception detection: Methods for finding fake news

This research surveys the current state‐of‐the‐art technologies that are instrumental in the adoption and development of fake news detection. “Fake news detection” is defined as the task of categorizing news along a continuum of veracity, with an associated measure of certainty. Veracity is compromised by the occurrence of intentional deceptions. The nature of online news publication has changed, such that traditional fact checking and vetting from potential deception is impossible against the flood arising from content generators, as well as various formats and genres.

[1]  Maria de Fatima Oliveira,et al.  Affective News and Networked Publics: The Rhythms of News Storytelling on #Egypt , 2012 .

[2]  Victoria L. Rubin,et al.  Truth and deception at the rhetorical structure level , 2015, J. Assoc. Inf. Sci. Technol..

[3]  R. Mooney,et al.  Impact of Similarity Measures on Web-page Clustering , 2000 .

[4]  Victoria L. Rubin,et al.  Towards News Verification: Deception Detection Methods for News Discourse , 2015 .

[5]  Shri Ramdeobaba,et al.  INFORMATION EXTRACTION USING DISCOURSE ANALYSIS FROM NEWSWIRES , 2014 .

[6]  Sushil Jajodia,et al.  Who is tweeting on Twitter: human, bot, or cyborg? , 2010, ACSAC '10.

[7]  Benjamin Waugh,et al.  Twitter Deception and Influence: Issues of Identity, Slacktivism, and Puppetry , 2014 .

[8]  Christopher D. Manning,et al.  Generating Typed Dependency Parses from Phrase Structure Parses , 2006, LREC.

[9]  Navneet Kaur,et al.  Opinion mining and sentiment analysis , 2016, 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom).

[10]  Johan Bollen,et al.  Computational Fact Checking from Knowledge Networks , 2015, PloS one.

[11]  D. Larcker,et al.  Detecting Deceptive Discussions in Conference Calls , 2012 .

[12]  Yimin Chen,et al.  News in an online world: The need for an “automatic crap detector” , 2015, ASIST.

[13]  Derek Greene,et al.  Distortion as a validation criterion in the identification of suspicious reviews , 2010, SOMA '10.

[14]  Claire Cardie,et al.  Negative Deceptive Opinion Spam , 2013, NAACL.

[15]  Carlo Strapparava,et al.  The Lie Detector: Explorations in the Automatic Recognition of Deceptive Language , 2009, ACL.

[16]  Luis Mateus Rocha,et al.  Correction: Computational Fact Checking from Knowledge Networks , 2015, PloS one.

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

[18]  Jeffrey T. Hancock,et al.  Hungry like the wolf: A word‐pattern analysis of the language of psychopaths , 2013 .

[19]  Jeffrey T. Hancock,et al.  Linguistic Traces of a Scientific Fraud: The Case of Diederik Stapel , 2014, PloS one.

[20]  Marilyn A. Walker,et al.  And That’s A Fact: Distinguishing Factual and Emotional Argumentation in Online Dialogue , 2015, ArgMining@HLT-NAACL.

[21]  Yejin Choi,et al.  Syntactic Stylometry for Deception Detection , 2012, ACL.

[22]  Hu Zhang,et al.  An Improving Deception Detection Method in Computer-Mediated Communication , 2012, J. Networks.