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

Authors

  • Vandna Batra Department of Computer Science & Engineering, Manav Rachna International Institute of Research and Studies, Faridabad, India
  • Suresh Kumar Department of Computer Science & Engineering, Manav Rachna International Institute of Research and Studies, Faridabad, India

DOI:

https://doi.org/10.48048/tis.2022.5611

Keywords:

Sentimental analysis, Radical activity, Machine learning, Deep learning

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

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Published

2022-08-01

Issue

Vol. 19 No. 15 (2022): Trends in Sciences, Volume 19, Number 15, 1 August 2022

Section

Research Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.