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A Novel Framework for Identifying Twitter Spam Data Using Machine Learning Algorithms
2020
Journal of Southwest Jiaotong University
Nowadays, Twitter has become one of the most popular social media in the world. However, its popularity makes it an attractive platform for spammers to spread spam. Twitter spam becomes a severe issue. It is referred to as unsolicited tweets containing malicious links that direct victims to external sites containing malware downloads, terrorists, phishing, drug sales, scams, etc. Previous studies have approached spam detection as a classification problem, high dimension, time-consuming problem,
doi:10.35741/issn.0258-2724.55.5.1
fatcat:5y5gobqrsvdpphw42jhhccxpcu