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Abstract
Social attributes of neighborhoods, like heritage, and low-level social disorder, are not reflected in official metrics such as deprivation indices. However, research suggests these attributes are important for understanding spatial variations in health and social outcomes. This exploratory study investigated whether recurring themes in local newspaper articles capture meaningful social characteristics that help explain neighborhood health resilience, defined as a dearth of illness after adjusting for deprivation. Topic modeling of geo-referenced texts identified and quantified 55 themes of commonly occurring words in Edinburgh, which capture salient neighborhood attributes. Correlations between the themes and domains of the Scottish Index of Multiple Deprivation (SIMD) were weak, suggesting that newspaper themes captured characteristics beyond those in the SIMD. Reassuringly, expected correlations were observed between crime metrics from newspapers and the SIMD domains. Stepwise regression modeling revealed theoretically plausible themes associated with neighborhood health resilience/vulnerability. Themes on heritage and community sports identity were positively associated with health resilience, whereas low-level social disorder (e.g., littering, antisocial behavior) and “local politics” were negatively associated. This study underscores the potential of using area-based topic modeling of newspaper texts to capture neighborhood aspects neglected in official statistics but could further explain spatial variations in neighborhood health outcomes.
Original language | English |
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Journal | Geographical Analysis |
Early online date | 26 May 2025 |
DOIs | |
Publication status | E-pub ahead of print - 26 May 2025 |
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- 1 Finished
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AIM-CISC: Artificial Intelligence and Multimorbidity: Clustering in Individuals, Space and Clinical Context (AIM-CISC)
Arakelyan, S. (Researcher), Guthrie, B. (Principal Investigator), Lyall, M. (Co-investigator), Lone, N. (Co-investigator) & Mercer, S. (Co-investigator)
1/08/21 → 30/07/24
Project: Research