Evidence map›Paper›PMID 41481755›Full record

ArticlePloS one2026

Spatial differentiation in public perception of peak summer heat based on microblog big data.

Yanling Sheng, Jiaqiao Zhen, Yihan Zhang, Dan Li

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yanling ShengSchool of Geography and Environmental Economics, Guangdong University of Finance & Economics, Guangzhou, China.ORCID https://orcid.org/0000-0002-1293-9037
Jiaqiao ZhenSchool of Geography and Environmental Economics, Guangdong University of Finance & Economics, Guangzhou, China.
Yihan ZhangSchool of Geography and Environmental Economics, Guangdong University of Finance & Economics, Guangzhou, China.
Dan LiSchool of Geography and Environmental Economics, Guangdong University of Finance & Economics, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The health problems caused by heat waves have attracted widespread global attention. High temperature is characterized by human perception before triggering discomfort. Understanding the public perception of high temperature based on social big data can help the relevant authorities to take appropriate countermeasures and reduce the risk of morbidity. Heat-related posts from Sina Microblog platform during the summer of 2023 are collected, and daily maximum temperature data of all meteorological stations across China from 1991 to 2023 is downloaded in the NCEI website. The relationship between public perception and temperature is investigated using the Latent Dirichlet Allocation (LDA) topic model, the heat attention index, and the heat perception model. The results reveal that 1) Heat-related microblogs are primarily concentrated in the southeastern regions of China. "Complaints About High Temperatures" is the most prominent topic. The most densely distributed regions for the four heat-related topics are Guangdong and Beijing. This distribution is closely related to the climate conditions, economic development levels, and internet penetration. 2) Heat attention index and daily maximum temperature of each province have a similar spatial distribution, while several provinces show discrepancies between the distribution of heat attention index and daily maximum temperature. 3) The daily maximum temperature corresponding to the lowest value of heat attention index in Guangdong is higher than that in other provinces. 4) There are obvious regional differences in the public's ability to heat tolerance and sensitivity. Regions with higher heat tolerance are mainly distributed in the southeastern part of China. People with higher heat sensitivity are mainly concentrated in the central and eastern regions of China. High temperature in Summer brings public discomfort and negative emotions. It is crucial to understand these regional perception differences and take timely measures to prevent heat-related health issues.

Indexed as

Big DataHot TemperaturePerceptionChinaHumansSeasonsSocial Media

Identifiers

PMID41481755
PMCPMC12758749

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LicenceCC BY
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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.