International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

Machine Learning and Bots Detection on Twitter

Norberto De Almeida Andrade, Giuliano Carlo Rainatto, Fontamara Lima, Genesio Renovato, Denis Gustavo Espacacherch Paschoal

Abstract: The social networking sites digital Become Increasingly popular, They also Attract the attention of spammers. This article, Twitter, the popular micro-blogging service, is an example of the Studied bot detection on digital social networking sites. Machine learning is Considered to regular spam robots Distinguish. To Facilitate the detection of spam, there are three aspects, the number of friends, number of followers and users. Data from all groups are extracted to Twitter. Three features Have Been added in 20 most recent user tweets. A set of current data is collected from the Twitter Object-telescope itself as it is Necessary to use two different methods. Evaluation experiments have Increased the risk of error on Twitter.

Keywords: Twitter, Machine Learning, Bots, TrustRank

How to Cite?: Norberto De Almeida Andrade, Giuliano Carlo Rainatto, Fontamara Lima, Genesio Renovato, Denis Gustavo Espacacherch Paschoal, "Machine Learning and Bots Detection on Twitter", Volume 8 Issue 9, September 2019, International Journal of Science and Research (IJSR), Pages: 944-947, https://www.ijsr.net/getabstract.php?paperid=ART20201061, DOI: https://dx.doi.org/10.21275/ART20201061

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