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Methods to Identify Fake News in Social Media Using Artificial Intelligence Technologies

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 858)

Abstract

Fake news (fake-news) existed long before the advent of the Internet and spread rather quickly via all possible means of communication as it is an effective tool for influencing public opinion. Currently, there are many definitions of fake news, but the professional community cannot fully agree on a single definition, which creates a big problem for its detection. Many large IT companies, such as Google and Facebook, are developing their own algorithms to protect the public from the falsification of information. At the same time, the lack of a common understanding regarding the essence of fake news makes the solution to this issue ideologically impossible. Consequently, experts and digital humanists specializing in different fields must study this problem intensively. This research analyzes the mechanisms for publishing and distributing fake-news according to the classification, structure and algorithm of the construction. Conclusions are then made on the methods for identifying this type of news in social media using systems with elements of artificial intelligence and machine learning.

Keywords

Fake news Fake-news Information falsification Social media Digital humanities Artificial intelligence Machine learning 

Notes

Acknowledgements

The reported study was funded by RFBR according to the research project № 18-311-00-125.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.ITMO UniversitySt. PetersburgRussia

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