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Robust Features for Detecting Evasive Spammers in Twitter
Conference proceeding   Peer reviewed

Robust Features for Detecting Evasive Spammers in Twitter

Muhammad Rezaul Karim and Sandra Zilles
ADVANCES IN ARTIFICIAL INTELLIGENCE, CANADIAN AI 2014, Vol.8436, pp.295-300
Lecture Notes in Computer Science
01/01/2014
DOI: https://doi.org/10.1007/978-3-319-06483-3_28

Abstract

Computer Science Computer Science, Artificial Intelligence Computer Science, Theory & Methods Science & Technology Technology
Researchers have designed features of Twitter accounts that help machine learning algorithms to detect spammers. Spammers try to evade detection by manipulating such features. This has led to the design of robust features, i.e., features that are hard to manipulate. In this paper, we propose and evaluate five new robust features.

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