Evolving Support Vector Machines using Whale Optimization Algorithm for spam profiles detection on online social networks in different lingual contexts

作者：

Highlights：

• A new classification approach based Support Vector Machine is proposed for detecting spammers on Twitter.

• The proposed approach reveals the most influencing features in the process of identifying spammers.

• Different lingual contexts are studied: Arabic, English, Spanish, and Korean.

摘要

•A new classification approach based Support Vector Machine is proposed for detecting spammers on Twitter.•The proposed approach reveals the most influencing features in the process of identifying spammers.•Different lingual contexts are studied: Arabic, English, Spanish, and Korean.

论文关键词：Spam detection,Feature selection,Social networks,Twitter,Classification,Whale Optimization Algorithm,WOA,Metaheuristic,Support Vector Machine,SVM,Multilingual

论文评审过程：Received 31 December 2017, Revised 25 March 2018, Accepted 21 April 2018, Available online 23 April 2018, Version of Record 11 May 2018.

论文官网地址：https://doi.org/10.1016/j.knosys.2018.04.025