Journal
HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES
Volume 9, Issue -, Pages -Publisher
SPRINGEROPEN
DOI: 10.1186/s13673-019-0185-6
Keywords
Social media; Sentiment classification; Emotions; Extremist sentiments; Terrorism; Extremist affiliations; Deep learning
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Funding
- Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah [G:277-830-1439]
- DSR
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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.
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