{
  "abstract": "Gendered activity patterns can create unequal exposure to urban environments, yet city-scale evidence rarely combines gender-specific happiness, nonlinear modelling, and local spatial variation. We analysed 678,120 geotagged Weibo posts across 33,591 500 m grids in Shanghai using LSTM-CNN sentiment classification, HRNet streetscape segmentation, XGBoost, SHAP, partial dependence plots, and spatially varying contributions. After screening, 320,618 female-labelled and 187,089 male-labelled posts entered the analysis. Sentiment classification achieved 0.942 accuracy; random-fold XGBoost R ² was 0.898 and 0.930 for female- and male-labelled happiness, and remained positive under spatial separation and the 20-user threshold. Results showed: (1) positive expression accounted for 73.64% of female-labelled posts and 74.30% of male-labelled posts. Female-labelled grid scores were higher and more variable (4.06 ± 2.13 versus 2.94 ± 1.71); both surfaces were spatially clustered (Moran’s I = 0.909 and 0.666) but modestly correlated ( r = 0.325; ρ = 0.273). (2) Population count and the Gini coefficient showed opposite correlations between groups. SHAP ranked NDVI first for the female-labelled model and Population count first for the male-labelled model, with Greenness, the Gini coefficient, and Distance to city center also prominent. (3) The same 5D dimension dominated only 43.3% of paired grids. Destination accessibility and Distance to Transit contributed more to female-labelled happiness in 95.1 and 84.0% of grids, whereas Design contributed more to male-labelled happiness in 68.0%. All five dimension-level differences were spatially clustered (Moran’s I = 0.571–0.788). These results locate contiguous gender differences in area-level happiness across Shanghai and provide evidence for locally targeted, gender-responsive urban and public-health planning.",
  "abstract_shown": true,
  "affiliations": [
    "College of Art, Wuyi University",
    "College of Landscape Architecture and Art, Fujian Agriculture and Forestry University"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Cuicui Ye"
    },
    {
      "affs": [
        1
      ],
      "name": "Zheng Ding"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9qghhv0r5bdyf.bib",
  "cited_by": 0,
  "doi": "10.3389/fpubh.2026.1962036",
  "fulltext_url": "https://europepmc.org/articles/PMC13713489",
  "id": "9qghhv0r5bdyf",
  "issns": [
    "2296-2565"
  ],
  "landing_url": "https://www.frontiersin.org/articles/10.3389/fpubh.2026.1962036/full",
  "language": "eng",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Original Research"
    ],
    [
      "openalex",
      "2307|Urban Green Space and Health"
    ]
  ],
  "openalex": "W7221796836",
  "pdf_url": "https://europepmc.org/articles/PMC13713489?pdf=render",
  "pmcid": "PMC13713489",
  "pmid": "42952840",
  "published": "2026-10-14",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/9qghhv0r5bdyf.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:22Z",
      "native_id": "10.3389/fpubh.2026.1962036",
      "source": "crossref",
      "url": "https://www.frontiersin.org/articles/10.3389/fpubh.2026.1962036/full"
    },
    {
      "first_seen": "2026-10-31T00:20:41Z",
      "native_id": "MED:42952840",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42952840"
    },
    {
      "first_seen": "2026-10-31T12:24:01Z",
      "native_id": "PMC13713489",
      "source": "pmc",
      "url": "https://doi.org/10.3389/fpubh.2026.1962036"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2307|Urban Green Space and Health",
      "subfield": "pharmacology-toxicology"
    }
  ],
  "title": "Using GeoXAI to reveal gender differences in the spatially nonstationary influence of built environment on area-level happiness",
  "title_text": "Using GeoXAI to reveal gender differences in the spatially nonstationary influence of built environment on area-level happiness",
  "type": "peer-reviewed",
  "updated_at": "2026-11-01T12:21:09Z",
  "url": "https://research.draconitic.com/paper/9qghhv0r5bdyf",
  "venue": "Frontiers in Public Health",
  "versions": []
}