Identification and classification of extremist-related tweets is a hot issue. Extremist gangs have been involved in using social media sites like Facebook and Twitter for propagating their ideology and recruitment of individuals. This work aims at proposing a terrorism-related content analysis framework with the focus on classifying tweets into extremist and non-extremist classes. Based on user-generated social media posts on Twitter, we develop a tweet classification system using deep learning-based sentiment analysis techniques to classify the tweets as extremist or non-extremist. The experimental results are encouraging and provide a gateway for future researchers.
CITATION STYLE
Ahmad, S., Asghar, M. Z., Alotaibi, F. M., & Awan, I. (2019). Detection and classification of social media-based extremist affiliations using sentiment analysis techniques. Human-Centric Computing and Information Sciences, 9(1). https://doi.org/10.1186/s13673-019-0185-6
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