The study discusses the modern possibilities of machine learning, which are becoming increasingly important due to the active development of social networks. Authors demonstrated the using of artificial intelligence and machine learning on an automated method for fake news identification. The problem with researching fake news is that they take many forms and spread through many channels, and their effectiveness today is significantly increasing because of the viral effect of social networks. The method is aimed at solving the tasks of automating the execution of processes in software and technical complexes by recognizing and analyzing tasks. They are presented as a system of facts in a text format and a ready-made code in accordance with the input data. The relevance of the development of this method is associated with the lack of comprehensive researches on the emergence of a large amount of unverified information in online spaces and the spread of fake news. In conclusion, authors indicated the possible directions for further studies which are based on objective recommendations for national government structures and for the EAEU as a whole.
Translated title of the contributionMACHINE LEARNING OPPORTUNITIES IN THE FIELD OF ELECTRONIC INTERACTION: RUSSIAN EXPERIENCE IN FAKE NEWS IDENTIFICATION
Original languageRussian
Pages (from-to)415-418
Number of pages6
Journal Евразийский юридический журнал
Issue number12(127)
StatePublished - 2018

ID: 36271479