Journal Article

A systematic literature review on spam content detection and classification

Elena Popescu, Daniela, Duraisamy, Jude Hemanth, Kaddoura, Sanaa, Chandrasekaran, Ganesh

2022

Overview

The presence of spam content in social media is tremendously increasing, and therefore the detection of spam has become vital. The spam contents increase as people extensively use social media, i.e ., Facebook, Twitter, YouTube, and E-mail. The time spent by people using social media is overgrowing, especially in the time of the pandemic. Users get a lot of text messages through social media, and they cannot recognize the spam content in these messages. Spam messages contain malicious links, apps, fake accounts, fake news, reviews, rumors, etc. To improve social media security, the detection and control of spam text are essential. This paper presents a detailed survey on the latest developments in spam text detection and classification in social media. The various techniques involved in spam detection and classification involving Machine Learning, Deep Learning, and text-based approaches are discussed in this paper. We also present the challenges encountered in the identification of spam with its control mechanisms and datasets used in existing works involving spam detection.

• Publisher: PeerJ. Ltd,PeerJ, Inc,PeerJ Inc
• Subject: Analysis / Artificial intelligence / Classification / Computational Linguistics / Control / Data Mining and Machine Learning / Datasets / Deep learning / Digital media / Disinformation / Epidemics / Germany / Language processing / Literature reviews / Machine learning / Messages / Natural Language and Speech / Natural language interfaces / Natural language processing / Network Science and Online Social Networks / Short message service / Social media / Social media analysis / Social networks / Spam (Junk email) / Spam Content / Spamming / Text messaging / Web sites