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Exploring the Relationship between Urban Youth Sentiment and the Built Environment Using Machine Learning and Weibo
Sutian Duan1, Zhiyong Shen1, Xiao Luo1
1Urban Mobility Institute, Tongji University, 4800 Cao'an Road, Shanghai 201804, China.
Summary
Urban youth sentiment is predominantly negative, with sadness strongly linked to the built environment. This research highlights how urban design impacts youth emotions and mental well-being.
Area of Science:
- Urban planning and design
- Environmental psychology
- Computational social science
Background:
- Growing importance of the built environment's impact on human experience.
- Emotional geography focuses on sentiments in urban spaces for public mental health.
- Lack of research on the relationship between urban youth sentiment and the built environment.
Purpose of the Study:
- To investigate the relationship between urban youth sentiments and the built environment.
- To analyze sentiment intensity and its correlation with built environment elements.
- To inform urban planning for enhanced youth well-being.
Main Methods:
- Utilized over 10,000 geolocated Sina Weibo comments from Shanghai (July 19-25, 2021).
- Employed a machine learning algorithm with an attention mechanism for sentiment analysis (label and intensity).
- Assessed ten built environment elements across five aspects at various scales.
Main Results:
- Overall sentiment among Shanghai youth tends to be negative.
- Sentiment intensity significantly correlates with most built environment elements at smaller scales.
- Sad sentiments are more closely linked to the built environment than happy sentiments, showing significant relationships with all elements.
Conclusions:
- Deep learning enhances sentiment classification accuracy, confirming the built environment's significant impact on emotions.
- Urban youth exhibit a higher proportion of extreme sentiments (happy and sad).
- Findings can guide cities in optimizing built environments to foster positive emotional experiences and improve youth well-being.
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