Using Social Media Data Mining To Understand The Public Perception of Coal In The United States

Author

Jie Shi Liew, Southern Illinois University CarbondaleFollow

Date of Award

9-1-2020

Degree Name

Master of Science

Department

Geography and Environmental Resources

First Advisor

Li, Ruopu

Abstract

Coal is a highly controversial energy source that has been widely perceived as environmentally harmful but socially important to regions with historical ties to coal production. Gauging public perception of coal is important to contemporary matters in energy policies like energy transition and the future of coal mining. Previous studies have demonstrated that public perception of coal can be affected by a multitude of geographic and social factors such as the distance to coal mining areas and political ideology. These studies predominantly relied on traditional survey approaches, which are typically cost prohibitive. With its growing popularity in public communication, social media has been recognized as an essential means of crowd-sourcing public perception and opinions. However, there is a general paucity of energy perception studies underpinned by social media, especially public perception of coal. Based on the Twitter data downloaded in August 2019, this thesis mapped the patterns of public perception of coal in the contexts of geographic spaces and social media network using data mining approaches. Generalized linear models were used to examine the quantitative relationship between public perception and explanatory geographic and social variables. The results demonstrate the geographic distance to coal mining regions, social network clusters, and certain social identities (i.e., environmental/renewable communities, Republicans, news and experts) have significant effects on coal-related sentiments by Twitter users, which are consistent with the results from other survey-based studies. The coal-related sentiments are found to be generally more similar among those Twitter users who are geographically distant, and socially close based on Twitter conversation network. This work suggests that social media may be a robust approach for future energy research in social science.