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.
Highlights
With the tremendous increase in the use of social network sites like Twitter and Facebook, online community is exchanging information in the form of opinions, sentiments, emotions, and intentions, which reflect their affiliations and aptitude towards an entity, event and policy [1,2,3]
To overcome the aforementioned limitations of state of the art study [7], we investigate deep learning-based sentiment analysis techniques, which have already shown promising performance across a large number of complicated problems in different domains like vision, speech and text analytics [9, 10]
We propose to apply long shortterm memory (LSTM)-Convolutional Neural Network (CNN) model, which works as follows: (i) CNN model is applied for feature extraction, and (ii) LSTM model receives input from the output of the CNN model and retains the sequential correlation by taking into account the previous data for capturing the global dependencies of a sentence in the document with respect to tweet classification into extremist and non- extremist
Summary
With the tremendous increase in the use of social network sites like Twitter and Facebook, online community is exchanging information in the form of opinions, sentiments, emotions, and intentions, which reflect their affiliations and aptitude towards an entity, event and policy [1,2,3]. The propagation of extremist content has been increasing and being considered as a serious issue in the recent era due to the rise of militant groups such as Irish Republican Army, Revolutionary Armed Forces of Colombia (FARC), Al Quaeda, ISIS (Daesh), Al Shabaab, Taliban, Hezbollah and others [4] These groups have spread their roots at the community levels and their networks are gaining control of social networking sites [5]. These networking sites are vulnerable and approachable platforms for the group strengthening, propaganda, brainwashing, and fundraising due to its massive impact on public sentiments and opinions Opinions expressed on such sites give an important clue about the activities and behavior of online users. It is beneficial in terms of classifying user’s extremist affiliation by filtering tweets prior to their onward transmission, recommendation or training AI Chatbot from tweets [6]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
