Systematics Review on the Application of Social Media Analytics for Detecting Radical and Extremist Group

Recently, social media platforms such as Twitter, Tumblr, Facebook, YouTube, blogs and discussion forums are being mistreated by radical groups to promote their ideologies and encourage radicalization. Social medias also have been used to create online extremist community and recruit new followers. In this paper work, the authors conduct a schematics literatures review on all available techniques and perform a comprehensive analysis on the application of social media analytic for detecting radical group to understand the circumstances, trends and its gaps. Further, the author provides the characterization, classification and meta-analysis in order to achieve a better understanding of the literature on the extremist detection through intelligent social media. It is found that for over the last 10 years many researchers have been conduct deep investigation on the use of social media analytics on predicting and identifying online radicalization. Besides, data source, features, geolocation, language, machine learning techniques, and tools have been applied on the recent literatures to detect those cyber-extremist activists. This paper also highlighting the performance measurement methods that have been used by researcher for detecting extremist group and radical communities. The goal of this research is to provide an academic base for ongoing research in the developing machine learning algorithm for detecting extremist and radical contents in social medias.