基于微博数据的北京市热点区域意象感知

发布时间：2018-03-23 12:26

  本文选题：地理空间数据　切入点：社交媒体　出处：《地理科学进展》2017年09期

【摘要】："城市意象"研究对城市文化感知、城市管理与规划、旅游资源开发等具有重要意义。近年来,随着智能移动终端和社交媒体的普及,产生了大量城市内包含有文本和地理位置等信息的社交媒体数据,涉及城市的各个区域,为开展城市意象的综合感知研究提供了新的途径。本文以2016年北京市带位置签到的新浪微博数据为例,在空间聚类发现热点区域的基础上,采用词频—逆文件频率(TF-IDF)与文档主题生成模型LDA两类典型的文本分析的方法,挖掘城市不同热点区域的主题,以感知北京市不同热点区域的社会文化功能和人群行为,并在此基础上通过对热点区域高频主题词进行共词聚类分析,深度挖掘北京市的总体意象。研究表明,运用文本挖掘及地理大数据分析的城市意象研究方法,能及时感知人群在城市不同场所的活动、态度、偏好,从而揭示城市的社会文化及功能特征,是对刻画城市物质形态的城市意象五要素模型的重要补充。此外,以北京市热点区域为例的实证研究结果对现实中的城市特色传承与空间品质塑造等有一定的启发意义。
[Abstract]:The study of "urban image" is of great significance to urban cultural perception, urban management and planning, tourism resource development, etc. In recent years, with the popularity of intelligent mobile terminals and social media, A large number of social media data in cities, including text and geographical location, have been generated, covering all parts of the city, This paper takes the data of Sina Weibo with location check-in in 2016 as an example, based on the spatial clustering to find hot spots, Two typical text analysis methods, word frequency inverse document frequency (TF-IDF) and document theme generation model (LDA), are used to excavate the themes of different hot spots in cities in order to perceive the social and cultural functions and crowd behavior of different hot spots in Beijing. On the basis of this, this paper makes a coterm clustering analysis of high-frequency thematic words in hot spots and deeply excavates the overall image of Beijing. The research shows that the research method of urban image is based on text mining and geographical big data analysis. The ability to perceive the activities, attitudes and preferences of people in different places in a city in time is an important supplement to the five-element model of city image, which can reveal the social, cultural and functional characteristics of the city. The results of the empirical research on the hot spot areas in Beijing are instructive to the inheritance of urban characteristics and the shaping of spatial quality in reality.
【作者单位】： 北京大学遥感与地理信息系统研究所;北京联合大学旅游信息化协同创新中心;
【基金】：国家自然科学基金项目(41501162) 北京市社会科学基金项目(17JDGLB002) 北京联合大学人才强校优选计划(BPHR2017DS08)~~
【分类号】：K901.6
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本文编号：1653447