Department of Geography and Spatial Sciences, University of Delaware, Newark, DE, 19716, USA.
Department of Political Science and International Relations, University of Delaware, Newark, DE, 19716, USA.
Sci Rep. 2023 Aug 3;13(1):12571. doi: 10.1038/s41598-023-39579-4.
The United Nations Sustainable Development Goal (SDG) target 11.7 calls for access to safe and inclusive green spaces for all communities. Yet, historical residential segregation in the USA has resulted in poor quality urban parks near neighborhoods with primarily disadvantaged socioeconomic status groups, and an extensive park system that addresses the needs of primarily White middle-class residents. Here we center the voices of historically marginalized urban residents by using Natural Language Processing and Geographic Information Science to analyze a large dataset (n = 143,913) of Google Map reviews from 2011 to 2022 across 285 parks in the City of Philadelphia, USA. We find that parks in neighborhoods with a high number of residents from historically disadvantaged demographic groups are likely to receive lower scores on Google Maps. Physical characteristics of these parks based on aerial and satellite images and ancillary data corroborate the public perception of park quality. Topic modeling of park reviews reveal that the diverse environmental justice needs of historically marginalized communities must be met to reduce the uneven park quality-a goal in line with achieving SDG 11 by 2030.
联合国可持续发展目标（SDG）目标 11.7 呼吁所有社区都能获得安全和包容的绿色空间。然而，美国历史上的居住隔离导致了经济社会地位群体主要处于不利地位的社区附近的城市公园质量较差，以及一个广泛的公园系统，满足了主要是白人中产阶级居民的需求。在这里，我们通过使用自然语言处理和地理信息科学来分析来自美国费城 285 个公园的 2011 年至 2022 年期间的大量谷歌地图评论数据集（n=143913），将历史上被边缘化的城市居民的声音置于中心位置。我们发现，居民中来自历史上处于不利地位的人口群体的人数较多的社区的公园在谷歌地图上的得分可能较低。根据航空和卫星图像以及辅助数据得出的这些公园的物理特征证实了公众对公园质量的看法。对公园评论的主题建模揭示了，必须满足历史上边缘化社区多样化的环境正义需求，以减少公园质量的不均衡，这一目标符合到 2030 年实现可持续发展目标 11 的目标。
