Analyzing Recent (2019) Kashmir Socio-Political Issue: A Voyant Sentiment Analysis of Tweets

Abstract

Computational Textual Analysis (CTA) is an effective way to analyze large texts by incorporating computational tools, such as, Voyant. The current study takes computer-assisted textual analysis (mixed method) to investigate the sentiments on tweets through Voyant computational method, in order to grasp the emotions of the global public who have tweeted about the recent (2019) Kashmir issue. This research is based on the conceptual framework of Ortony, Clore, and Collins (OCC) model and the keyword approach. For this purpose, different tweets have been analyzed to check the level of sentiments as either positive, negative or neutral. The findings suggested that sentiments were neutral towards the issue of Kashmir and negative towards the Indian government. Voyant has also presented the word count, density, and correlation of phrases within the larger text context. Voyant procedures like; cirrus, trend and summary showed the results based on quantitative and qualitative measures. These toolsets are easy to use without any programming skills and seem to be the best for researchers of social sciences and humanities who are trying to work in digital humanities. The study also recommends Voyant as an operative tool for textual analysis for Computational Linguists, Postmodernism, Critical Discourse Analysis, English Literature, History, Sociology, Theology, and any other field of knowledge that falls under the domain of digital humanities.