Adnan Ali1, Jinlong Li1, Huanhuan Chen1, Uzair Aslam Bhatti2, Asad Khan3,*
Intelligent Automation & Soft Computing, Vol., , DOI:10.32604/iasc.2023.041645
Abstract Spammer detection is to identify and block malicious activities performing users. Such users should be identified
and terminated from social media to keep the social media process organic and to maintain the integrity of online
social spaces. Previous research aimed to find spammers based on hybrid approaches of graph mining, posted
content, and metadata, using small and manually labeled datasets. However, such hybrid approaches are unscalable,
not robust, particular dataset dependent, and require numerous parameters, complex graphs, and natural language
processing (NLP) resources to make decisions, which makesspammer detection impractical for real-time detection.
For example, graph mining requires neighbors’ information,… More >