Methods to Identify Fake News in Social Media Using Machine Learning
| Autor: | Denis Zhuk, Arsenii Tretiakov, Andrey Gordeichuk |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: | |
| Zdroj: | Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 426, Iss 22, Pp 401-404 (2018) |
| Druh dokumentu: | article |
| ISSN: | 2305-7254 2343-0737 |
| Popis: | Fake news (fake-news) existed long before the advent of the Internet and spread rather quickly by all possible means of communication being 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 one, what creates a big problem for their detection. Many large IT companies, such as Google and Facebook, are developing their own algorithms to protect the public from informational falsification. At the same time, the lack of a common approach to understanding the essence of fake news makes the solution of this issue ideologically impossible. This problem requires to be seriously studied by specialized experts and scientists from different fields. This research analyzes the mechanisms of publication and distribution of fake-news, gives their classification, structure and algorithm of construction. The researchers decide on the methods of identifying this type of news in social media with the help of systems featuring the elements of artificial intelligence and machine learning. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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