Sentiment Analysis of Global Warming Using Twitter Data
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Global warming or climate change is one of the most discussed topics of the decade. Some people think global warming is a severe threat to the planet whereas some people think, it is a hoax. The goal of this paper is to analyze how people’s perceptions have changed over the years for past decade using sentiment analysis on Twitter data. Twitter is a social networking platform with 320 million monthly active users. I have captured tweets with words such as “Global warming”, “Climate Change” etc. and applied sentiment analysis to classify them as positive, negative or neutral tweets. I have trained Naïve Bayes Classifier, Multinomial Naïve Bayes Classifier and SVM classifiers on several training datasets to optimize for best accuracy. The methodology with best accuracy rate has been used to find out people’s perception of global warming over the years using Twitter data.