People's attitudes toward hydraulic fracturing (i.e., "fracking") to extract fossil fuels can be shaped by factors associated with socio-demographics, economic development, social equity and politics, environmental impacts, and fracking-related information obtainment. Existing research typically conducts surveys and interviews to study public attitudes toward fracking among a small group of individuals in a specific geographic area, where limited samples may introduce bias. Here, we compiled geo-referenced social media big data from Twitter during 2018-2019 for the entire United States to present a more holistic picture of people's attitudes toward fracking. We used a multiscale geographically weighted regression (MGWR) to investigate county-level relationships between the aforementioned factors and percentages of negative tweets concerning fracking. Results clearly depict spatial heterogeneity and varying scales of those associations. Counties with higher median household income, larger African American populations, and/or lower educational level are less likely to oppose fracking, and these associations show global stationarity in all contiguous U.S. counties. Eastern and Central U.S. counties with higher unemployment rate, counties east of the Great Plains with less fracking sites nearby, and Western and Gulf Coast region counties with higher health insurance enrollments are more likely to oppose fracking activities. These three variables show clear East-West geographical divides in influencing public perspective on fracking. In counties across the southern Great Plains, negative attitudes toward fracking are less often vocalized on Twitter as the share of Republican voters increases. These findings have implications for both predicting public perspectives and needed policy adjustments. The methodology can also be conveniently applied to investigate public perspectives on other controversial topics.
Keywords: Fracking; multiscale geographically weighted regression (MGWR); public perspective; social media; spatial heterogeneity.