Characterizing climate change sentiments in Alaska on social media
Year: 2024
Type: article
Abstract: The profound impacts of climate change have spurred global concerns. Yet, public perceptions of this issue exhibit significant variations rooted in local contexts. This study investigates public perceptions of climate change in Alaska on Twitter and explores their connections with local socioeconomic and environmental factors. Using geo-located tweets from 2014 to 2017, we identified a collection of climate-related tweets using a deep learning framework. Employing lexicon-based sentiment analysis, we quantified the sentiments with positive and negative scores, further enriched by extracting eight core emotions expressed in each tweet. Furthermore, we applied regression models to assess the influence of regional socioeconomic and environmental attributes on climate-related sentiments at the census tract level. Our findings reveal an overall upward trajectory of Alaska's Twitter-expressed climate change sentiments over time, particularly during the summer months. Insights into the interplay between local demographics and environmental features and climate change perceptions include: (1) Census tracts with higher Native Alaskan or American Indian populations tend to express more negative sentiments, (2) the inclusion of road density stands out as a significant factor, suggesting that climate change is seen/discussed more in areas with more dense-built infrastructure, and (3) the presence of mixed emotions exhibits a profound connection with climate change sentiments-i.e., emotions of disgust and surprise are inversely related, whereas sadness and trust demonstrate positive associations. These outcomes underscore an evolving situation awareness of climate change among individuals, emphasizing the need to consider local factors in understanding public perceptions of this global issue.
Source: Digital Geography and Society
Authors: Junjun Yin, Matthew Brooks, Donghui Wang, Guangqing Chi
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $1,220
Awards: RR: The Generalizability and Replicability of Twitter Data for Population Research, G28523178, Belmont Forum Collaborative Research: RETRACE-ResilienceS to Climate Risks: Lessons from Arctic and Pacific Communities, NNA Track 1: Pursuing Opportunities for Long-term Arctic Resilience for Infrastructure and Society (POLARIS), G5284736384, RAPID: Using Mobile Phone Data to Understand the Impacts of the COVID-19 Pandemic on Food Assistance Use in Alaska, G7555060587, NNA Research: Collaborative Research: Arctic, Climate, and Earthquakes (ACE): Seismic Resilience and Adaptation of Arctic Infrastructure and Social Systems amid Changing Climate
OpenAlex ID: W4405686255