The study used Natural Language Processing and Geographic Information Science to analyze a dataset of 143,913 Google Map reviews from 2011 to 2022 across 285 parks in Philadelphia.
Scientific Reports · 4 authors, 4 centres
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The study used Natural Language Processing and Geographic Information Science to analyze a dataset of 143,913 Google Map reviews from 2011 to 2022 across 285 parks in Philadelphia.
The study used Natural Language Processing and Geographic Information Science to analyze a dataset of 143,913 Google Map reviews from 2011 to 2022 across 285 parks in Philadelphia. The central finding is that parks in neighborhoods with higher proportions of Black and Hispanic residents, lower socioeconomic status groups, children, and people with disabilities are likely to receive lower scores on Google Maps. Topic modeling revealed that park condition and safety are the most common topics in negative reviews for these areas. Limitations include the reliance on Google Maps reviews, which may not represent all residents, and the inability to link reviews to individual demographics. The authors suggest that park planning should focus on improving maintenance, safety, and amenities in underserved neighborhoods to address these environmental justice concerns.