Identifying Radical Activity on Social Digital Platform: A Machine Learning Approach

Abstract

The social media in digital form over internet is getting popularity in recent years. This digital platform is being used by many to share their thought or opinion. Though these social media had given results too many good causes, there are some users are present on these platforms for radical activities. In this paper, the tweets form the digital social platform twitter is taken for analysis based on radical keywords. The data is collected in form of tweets are analyzed using different machine learning algorithms and a comparative analysis is done. The proposed work concludes the best machine learning algorithms for analysis of such data and the new words came in light for the collected dataset. The deep learning model are also implemented and tested for sentimental analysis.
 HIGHLIGHTS
 
 Radical keywords-based message collection from social platforms
 Application of various machine learning and deep learning algorithms trained using collected datasets
 Discovery of new temporal words
 Identification of radical messages floating on social platforms
 Identifying the best performing machine learning and deep learning algorithm for radical message analysis
 
 GRAPHICAL ABSTRACT