Topic Modelling and Sentiment Analysis of Global Warming Tweets: Evidence From Big Data Analysis

With the increasing extreme weather events and various disasters, people are paying more attention to environmental issues than ever, particularly global warming. Public debate on it has grown on various platforms, including newspapers and social media. This paper examines the topics and sentiments of the discussion of global warming on Twitter over a span of 18 months using two big data analytics techniques: topic modelling and sentiment analysis. There are seven main topics concerning global warming frequently debated on Twitter: factors causing global warming, consequences of global warming, actions necessary to stop global warming, relations between global warming and COVID-19, global warming's relation with politics, global warming as a hoax, and global warming as a reality. The sentiment analysis shows that most people express positive emotions about global warming, though the most evoked emotion found across the data is fear, followed by trust. The study provides a general and critical view of the public's principal concerns and their feelings about global warming on Twitter.

Automated summary

This study examines the topics and sentiments of global warming discussion on Twitter using big data analytics techniques. It identifies seven main topics frequently debated, including factors causing global warming, consequences of global warming, actions necessary to stop global warming, and other related issues. The sentiment analysis reveals that most people express positive emotions about global warming, with fear being the most evoked emotion.