Evidence map›Paper›PMID 38390408›Full record

ArticleFrontiers in psychology2024

Exploring the non-linear relationship and synergistic effect between urban built environment and public sentiment integrating macro- and micro-level perspective: a case study in San Francisco.

Pingge He, Bingjie Yu, Jiexi Ma, Keqian Luo, Siting Chen, Zhongwei Shen

Abstract read
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Article in Frontiers in psychology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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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

6 authors.

Pingge HeSchool of Architecture, Southwest Jiaotong University, Chengdu, China.
Bingjie YuSchool of Architecture, Southwest Jiaotong University, Chengdu, China.
Jiexi MaSchool of Architecture, Southwest Jiaotong University, Chengdu, China.
Keqian LuoSchool of Architecture, Southwest Jiaotong University, Chengdu, China.
Siting ChenSchool of Architecture, Southwest Jiaotong University, Chengdu, China.
Zhongwei ShenSchool of Architecture, Southwest Jiaotong University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Public sentiment can effectively evaluate the public's feelings of well-being in the urban environment and reflect the quality of the spatial environment to a certain extent. Previous studies on the relationship between public sentiment and urban built environmental factors have yielded meaningful results. However, few studies have focused on the effect of micro-built environment on public sentiment at the street level, which directly shapes people's perceptions. In addition, the nonlinear relationship and synergistic effect among urban built environmental factors have been commonly disregarded in previous studies, resulting in an incomplete understanding of the impact of urban built environment on public emotions. Therefore, this paper takes San Francisco as a study case to explore the complex relationship between urban built environmental factors and public emotions. Specifically, this paper measures the polarity of public emotions through sentiment analysis on Twitter data, establishes a comprehensive built environment index system from both macro- and micro- perspectives, and subsequently explores the complex relationship between the urban built environment and public sentiment through the OLS model and Shapley Additive Explanation algorithm. Results show that: (1) micro-built environmental factors have a significant influence on public emotion, although they have been frequently ignored. (2) Public sentiment tends to be more positive in areas with recreation facilities, mixed land use, rich street view visual environment, suitable thermal and acoustic environment, balanced income, and a suitable degree of high population density. (3) A nonlinear relationship and threshold effect exist between the built environmental variables and the semantic orientations of public emotion. Environment improvement strategies based on the synergic effect between variables can effectively promote the generation of positive emotions. Our empirical findings can offer valuable insights to promote feelings of well-being and foster an urban development approach through strategic interventions within the urban built environment.

Indexed as

non-linearitypublic sentimentstreet visual environmentsynergistic effectthermal comforturban built environment

Identifiers

PMID38390408
PMCPMC10881791

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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.