Sentiment analysis of facebook posts on Kolkata police page and public sentiment

Abstract

This paper is an analysis of the comments posted on the facebook page of Kolkata Police through sentiment analysis tools to understand people's attitudes towards Kolkata Police during lockdown I & II in the state of West Bengal in India. These platforms keep people digitally connected. Social media also has given consumers a virtual soapbox, from where they can convey their opinions. Every day huge volumes of text data are getting generated on social platforms. While humans instantly understand the sentiment behind a single comment, how should we cope with the explosion of content shared on social platforms? It is extremely challenging to analyse the massive amount of unstructured text data manually. Here we need tools to help us. AI-powered sentiment analysis tools use natural language processing techniques to analyse the online conversation and underlying context - positive, neutral, or negative. Sentiment analysis tools mimic human brains and allow us to get the sentiment behind online content. In this study, researcher has used rule-based sentiment analysis techniques (TextBlob and Valence Aware Dictionary and Sentiment Reasoner or VADER) to detect the public sentiment towards the service of Kolkata police during COVID lockdown phase I & II (March 22, 2020, to May 3, 2020)