Carbon taxation is an effective emission reduction policy but it is unpopular, and little is known why people oppose it. In response to the lack of timely updates on people's perceptions of the issue at hand, this study uses a sample of Twitter data to discover the underlying factors of discourses related to carbon taxes.
The bisecting k-means algorithm and correspondence analysis are used to cluster tweets based on keywords that symbolize people's attitudes. The results show that the main driving factors for attitudes towards carbon taxes are trust in the government, Education, and the perceptions of taxation's impact on individuals and businesses.
The estimated importance of these factors are 35%, 24%, 22%, 17% respectively. Sentiment analysis reveals the negative emotions towards carbon taxes in most of the studied countries regardless of whether the policy has been implemented or not.
The sentiments toward the factors are also negative. In addition, we found a positive correlation between attitudes towards these factors and attitudes towards carbon taxation.
The correlation degree is consistent with the results of the correspondence analysis. The sentiments toward these taxes worsen in countries where the perceived cost on individuals and businesses is higher and trust in government is lower.
Our study points out the importance of social media as a real-time source of data for environmental policy input and proves the need for better citizen consultation and interest assurance before introducing carbon taxation. (C) 2021 Institution of Chemical Engineers. Published by Elsevier B.V.
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