Evidence map›Paper›PMID 40547048›Full record

ArticleDigital geography and society2025

Characterizing climate change sentiments in Alaska on social media.

Junjun Yin, Matthew Brooks, Donghui Wang, Guangqing Chi

Abstract read
In one paragraph

Article in Digital geography and society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Junjun YinPopulation Research Institute and Social Science Research Institute, The Pennsylvania State University, University Park, PA 16802, USA.
Matthew BrooksDepartment of Sociology, Florida State University, Tallahassee, FL 32306, USA.
Donghui WangCenter for Population and Development Studies, School of Sociology and Population Studies, Renmin University of China, Beijing 100872, China.
Guangqing ChiPopulation Research Institute and Social Science Research Institute, The Pennsylvania State University, University Park, PA 16802, USA.

Funding

The Population Research Institute: Development CoreP2CHD041025 · NICHD · PENNSYLVANIA STATE UNIVERSITY, THE · PI Sarah Damaske · 2016 to 2026
$9.0M
NICHD NIH HHS P2C HD041025
6 · The paper itself

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.

Indexed as

Big dataClimate changeSentiment analysisSocial mediaSpatial-temporal analysis

Identifiers

PMID40547048
PMCPMC12180577

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.