How do residents perceive urban parks? A cross-geographic comparison based on online reviews

Abstract

Clarifying the quality elements that have a significant impact on public perception is a prerequisite for improving the quality of parks, and comparative cross-regional studies can help to identify local landscape preferences and formulate specialized development strategies. Using online review data and natural language processing methods, this study explores how Chongqing and Chengdu residents' perceptions of environmental features of urban parks affect their overall satisfaction. The results show that: (1) There are 16 (Chongqing) and 13 (Chengdu) environmental features that residents pay attention to in urban parks, and the two places pay the highest attention to the natural features of urban parks. In addition, Chongqing residents pay more attention to the recreational services of urban parks, while Chengdu residents pay more attention to the aesthetics and culture of urban parks. (2) Positive environmental factors increase visitors' satisfaction, but this effect decreases with increasing frequency of perceived, while negative factors continue to have a negative impact on satisfaction. Through online text data and natural language processing technology, the public's perception of parks can be analyzed on a large scale, in depth, and with high accuracy, providing guidance for urban sustainable construction and characteristic style extraction.

Keywords

Urban parks / Landscape perception / Machine learning / Natural language processing (NLP) / Regional comparison / Social media data

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