Author:
Ahmad Shakeel,Asghar Muhammad Zubair,Alotaibi Fahad M.,Awan Irfanullah
Abstract
Abstract
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.
Funder
The Deanship of Scientific Research
Publisher
Springer Science and Business Media LLC
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