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Rural‐Urban Differences in the Determinants of Subjective Well‐Being Among X/Twitter Users in the United States.

Twitter Sentiment Geographical Index (TSGI) has been proposed to complement traditional surveys to measure subjective well‐being (SWB) at the US county level. Our study aims to investigate determinants of TSGI‐measured SWB in rural and urban US counties. Using the Classification and Regression Tree,...

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Published in:Population Space & Place Vol. 31; no. 1; pp. 1 - 17
Main Authors: Jiang, Wenting, Zhang, Mengxi, Wu, Connor Y. H., Dong, Weichuan
Format: Article
Published: Wiley-Blackwell Jan2025
Subjects:
X Corp.
Rural population
Microblogs
Real property tax
Regression trees
Random forest algorithms
Regression analysis
Online Access:View this record in EBSCOhost
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      dt: Jan2025
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      pub: Wiley-Blackwell
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        10.1002/psp.2861
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        atl: Rural‐Urban Differences in the Determinants of Subjective Well‐Being Among X/Twitter Users in the United States.
      aug:
        au:
          Jiang, Wenting
          Zhang, Mengxi
          Wu, Connor Y. H.
          Dong, Weichuan
        affil:
          Department of Management Science and Information Systems, Oklahoma State University, Oklahoma,, USA
          Department of Health Systems and Implementation Science, Virginia Tech Carilion School of Medicine, Virginia,, USA
          Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland Ohio,, USA
      su:
        X Corp.
        Rural population
        Microblogs
        Real property tax
        Regression trees
        Random forest algorithms
        Regression analysis
      sug:
        subj:
          Rural population
          Microblogs
          X Corp.
          Lessors of Other Real Estate Property
          Real property tax
          Regression trees
          Random forest algorithms
          Regression analysis
      keyword:
        classification and regression tree
        random forest analysis
        social media
        SWB
        Twitter Sentiment Analysis
        classification and regression tree
        random forest analysis
        social media
        SWB
        Twitter Sentiment Analysis
      ab: Twitter Sentiment Geographical Index (TSGI) has been proposed to complement traditional surveys to measure subjective well‐being (SWB) at the US county level. Our study aims to investigate determinants of TSGI‐measured SWB in rural and urban US counties. Using the Classification and Regression Tree, we identified phenotypes or county‐level characteristics associated with high SWB. Counties with newer homes were the top characteristic of high SWB in both urban and rural areas. Counties of the identical phenotypes tend to concentrate geographically, with the most favorable phenotypes clustered in the South. Random Forest analysis identified additional characteristics of high SWB, including higher population density in rural areas and lower real estate tax ratio in urban areas. Our results yield a comprehensive understanding of determinants of SWB at the local level, guiding evidence‐based policy decisions and community initiatives to improve well‐being in target populations.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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