Study of radical views on social media: Classification and group dynamics analysis
Document Type
Conference Proceeding
Source of Publication
2021 6th International Conference on Smart and Sustainable Technologies, SpliTech 2021
Publication Date
9-8-2021
Abstract
Social media platforms have changed the way extremist groups recruit, influence and potentially radicalize users online. Radicalization has drawn the attention of many researchers worldwide with its increasing presence on social media. Therefore, the ability to identify and classify radical views online and their potential role in radicalizing individuals is of critical importance. In this work, we address this challenge by combining a number of machine learning and natural language processing techniques such as sentiment analysis, named entity recognition, clustering, opinion leader identification, and social circle analysis to gain insights about radical views related to extreme nationalism, and understand the social dynamics underpinning extremists' related interactions. The proposed approach was implemented and tested on more than 259, 000 tweets collected over a five-year span. The different analysis steps were presented and the results obtained were analyzed.
DOI Link
ISBN
9789532901122
Disciplines
Computer Sciences
Keywords
Classification and clustering, Group dynamics, Nationalism, Radical views, Social media analytics
Scopus ID
Recommended Citation
Yasin, Rand; Lutfi, Saad; Imene, Ajala; Oroumchian, Farhad; El Barachi, May; and Mathew, Sujith Samuel, "Study of radical views on social media: Classification and group dynamics analysis" (2021). All Works. 4644.
https://zuscholars.zu.ac.ae/works/4644
Indexed in Scopus
yes
Open Access
no