Open AccessChennai Floods 2021: Sentiment Analysis of Twitter Data using Tweepy and TextBlob
Author(s) -
Raghav Tinnalur Swaminathan
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.39391
Subject(s) - sentiment analysis , computer science , variety (cybernetics) , visualization , data science , polarity (international relations) , social media , information retrieval , data mining , world wide web , natural language processing , artificial intelligence , genetics , biology , cell
The rise in the usage of Twitter for the exclamation of the problems worldwide and also as a ‘review system,’ where the customers can directly hold an entity responsible in front of the public by tweeting and tagging them, gives them immense power and counts towards being an advantage for researchers to analyze such data that can be scraped and used through APIs for a variety of purposes. Through this research, our motive is to analyze the 2021 Chennai floods with data sourced from twitter to understand the public sentiment during the 14-day span. The same is achieved with the help of Tweepy to authenticate data extraction from Twitter and TextBlob, for the classification of sentiment tags - positive, negative, and neutral. The result of this study focuses on the visualization of our findings, with various charts and metrics indicating the sentiment of the tweets we have scraped and analyzed. Keywords: Sentiment Analysis, WordCloud, Subjectivity, Polarity, Chennai Floods