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  被引量:4

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

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作  者:刘明浩 李鹍[1] 李晨慧 LIU Minghao;LI Kun;LI Chenhui

机构地区:[1]武汉大学城市设计学院

出  处:《西部人居环境学刊》2023年第2期24-29,共6页Journal of Human Settlements in West China

基  金:国家科技基础性工作专项(2013FY11250);国家自然科学基金青年科学基金项目(51208389)。

摘  要: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 emotion

关 键 词:健康城市 情绪分布 绿地率 职住关系 建成环境 

分 类 号:TU984[建筑科学—城市规划与设计]

 

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