Evaluating the social media attributes of urban blue-green open space using a back propagation neural network

XU Haishun, QIAN Chen, QIN Xue

JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2024, Vol. 48 ›› Issue (6) : 193-200.

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南京林业大学学报（自然科学版）
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JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2024, Vol. 48 ›› Issue (6) : 193-200. DOI: 10.12302/j.issn.1000-2006.202306020

Evaluating the social media attributes of urban blue-green open space using a back propagation neural network

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Abstract

【Objective】Through the analysis of the needs and activity patterns of urban blue-green open space (BGOS) users, the social media attributes of urban BGOS can best serve people were identified. The aim was to construct a scientifically based evaluation system that enhanced the “People-BGOS-Society” relationship and provide a reference for corresponding management planning.【Method】Based on literature research, field surveys, and network data collection, from the perspective of BGOS as the urban social medium, an evaluation model of the social media attributes of urban BGOS was constructed based on four dimensions: space background, connection type, participation mode, and spatial significance. Taking three urban parks in Nanjing as an examples, a back propagation (BP) neural network model was used for model verification and a weighted quantitative analysis.【Result】By studying the survey data, the BP neural network evaluated the social media attributes of urban BGOS. The evaluation model included four first-level indicators and 12 second-level indicators. The first-level indicators included spatial background, connection type, participation mode, and spatial significance, among which spatial background (weight 0.440) was the key factor for evaluating the social media attributes. Among the secondary indicators, the natural support level (weight 0.157) had the greatest impact, followed by infrastructure perfection (weight 0.127), microclimate comfort (weight 0.125), and local identity (weight 0.121), while the remaining parameters showed relatively little impact. The quality of the spatial background was the basis for attracting users to carry out social activities. The close “People-BGOS-Society” relationship helped to improve the spatial level of social media attributes.【Conclusion】This study combined sociology with the field of landscape architecture. From the perspective of the relationship between people and space, the application of a BP neural network model was a novel research concept and methods were developed for the identification and evaluation of the social benefits of BGOS.

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blue-green open space (BGOS) / BP neural network / social media / attribute evaluation / Nanjing City

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XU Haishun , QIAN Chen , QIN Xue. Evaluating the social media attributes of urban blue-green open space using a back propagation neural network[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY. 2024, 48(6): 193-200 https://doi.org/10.12302/j.issn.1000-2006.202306020

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