基于微博大数据的居民情绪与建成环境关系研究——以武汉市为例

Research on the Relationship Between Residents’Emotions and Built Environment Based on Weibo Data:Taking Wuhan City as an Example

本研究使用腾讯云自然语言处理技术对微博数据中的居民情绪进行了识别,得到了不同微博发送点位的情绪值,对不同类型情绪的空间分布特征进行了分析,并采用回归方法分析了社区的平均微博情绪指数与社区绿地率、职住比之间的关系。研究主要有如下发现:居民的情绪整体偏向积极,积极情绪主要分布在景点和休闲相关设施的周边;当社区内科教文化、公司企业、医疗设施类POI密度增加到一定阈值后,居民情绪呈下降趋势;当社区绿地率在39.3%附近时,社区平均情绪指数情况较低,而职住关系指数与微博情绪指数呈反比关系。

Emotions and moods are essential components of mental health indicators,reflecting a person’s psychological state and well-being.However,mental health issues are prevalent in our country,with many people not meeting mental health standards,which calls for attention to be given to mental health,and one way to do that is through creating a pleasant built environment that can significantly improve people’s emotions and consequently improve their mental health status.While a pleasant built environment can be beneficial,its traditional research methods,like questionnaires,are often time-consuming,laborious,and non-immediate.However,with the development of big data technology,social media information has facilitated the study of the relationship between residents’moods and the built environment,which has some immediacy.This method has opened up new possibilities for studying the built environment’s impact on emotions and moods.To conduct this study,it firstly obtained relevant built environment data and sentiment values of the microblog text.It used Tencent Cloud natural language processing technology to identify the residents’sentiment in the microblog data of Wuhan city in July 2022 and derive the sentiment values of different microblog sending locations.It also used the POI and AOI of Gaode Map with Google satellite map information to obtain the green space rate and building information.Secondly,it analyzed the spatial distribution characteristics of different types of emotions and summarized the areas of concentration of positive and negative emotions,respectively.In addition,we used the most basic administrative unit in China’s administrative division,i.e.,community,as the unit of analysis and used the geographic probe to determine the built environment characteristics that have a relationship with the microblogging sentiment index.It classified the unit of analysis into seven classes according to the quantile of the built environment.This helped us determine the built environment’s impact on emotions and moods.The results of our study revealed that Wuhan residents’emotions are positive overall,with positive emotions mainly distributed around attractions and leisure-related facilities.However,when the density of science,education,culture,corporate enterprises,and medical facilities POIs in the community is increased to a certain threshold,residents’emotions tend to decline.This highlights the importance of having a balance between different types of facilities in a community.Furthermore,it constructed a mathematical model of sentiment,community green space rate,and occupational and residential relationship index.This study highlights the importance of studying the relationship between the built environment and emotions and provides recommendations for improving emotional positivity in communities.The findings showed that when the community green space rate was around 39.3%,the average community sentiment index situation was low,while the occupational and residential relationship index was inversely related to the microblogging sentiment index.This highlights the importance of green spaces in communities and the need to balance occupational and residential areas.To improve residents’emotional positivity,it recommends increasing the green space rate in areas with high green space rates,such as parks to improve emotional positivity.In addition,the daytime vitality of suburban communities should be increased by balancing transportation,reducing commuting distances,and increasing infrastructure in lagging communities to improve the job-to-residence ratio to increase residents’emotional positivity.At the policy level,the number of POIs in the central city can be reduced by“reducing the burden”in order to relieve the pressure on students and increase their emotional value.In conclusion,emotions and moods are essential components of mental health indicators,and a pleasant built environment can significantly improve people's emotions and mental health.