Stephen Afrifa1,2,*, Vijayakumar Varadarajan3,4,5,*, Peter Appiahene2, Tao Zhang1, Richmond Afrifa6
Computer Systems Science and Engineering, Vol.48, No.6, pp. 1625-1639, 2024, DOI:10.32604/csse.2024.055084
- 22 November 2024
Abstract Users of social networks can readily express their thoughts on websites like Twitter (now X), Facebook, and Instagram. The volume of textual data flowing from users has greatly increased with the advent of social media in comparison to traditional media. For instance, using natural language processing (NLP) methods, social media can be leveraged to obtain crucial information on the present situation during disasters. In this work, tweets on the Uttarakhand flash flood are analyzed using a hybrid NLP model. This investigation employed sentiment analysis (SA) to determine the people’s expressed negative attitudes regarding the disaster. More >