Chao Li, Zhongying Zhao, Shuguang Liu, Ling Yin, Jun Luo
{"title":"Relationships between geographical cluster and cyberspace community: A case study on microblog","authors":"Chao Li, Zhongying Zhao, Shuguang Liu, Ling Yin, Jun Luo","doi":"10.1109/Geoinformatics.2012.6270315","DOIUrl":null,"url":null,"abstract":"As a major online interactive platform, microblogs have accumulated numerous data about people's interactive behaviors, which have attracted many researchers to study these data. However, the existing studies mainly focus on the community structure detection or information propagation from the conventional perspective of social network analysis. Few studies have investigated the relationships between people's online social behaviors and their geographical location information over Social Media. In this paper, we aim to analyze the relationships between people's online social activities and their geographical locations in Tencent-Microblog. We first make a statistical summary on different geographical locations and the number of users at each location. We find that the frequency distribution of the number of recorded locations from an individual follows a power law. Considering each individual's posting frequency and staying time on a certain location, we define a main location of an individual. In order to study the relations between communities and location clusters, we propose the index of location entropy to measure the degree of dispersion of the locations in each community, and the index of community entropy to measure the degree of dispersion of the communities in each location cluster. More importantly these two indexes can potentially help measure the influential power for the topic community and monitor the active degree of people's online social behavior in a location cluster.","PeriodicalId":259976,"journal":{"name":"2012 20th International Conference on Geoinformatics","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 20th International Conference on Geoinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Geoinformatics.2012.6270315","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
As a major online interactive platform, microblogs have accumulated numerous data about people's interactive behaviors, which have attracted many researchers to study these data. However, the existing studies mainly focus on the community structure detection or information propagation from the conventional perspective of social network analysis. Few studies have investigated the relationships between people's online social behaviors and their geographical location information over Social Media. In this paper, we aim to analyze the relationships between people's online social activities and their geographical locations in Tencent-Microblog. We first make a statistical summary on different geographical locations and the number of users at each location. We find that the frequency distribution of the number of recorded locations from an individual follows a power law. Considering each individual's posting frequency and staying time on a certain location, we define a main location of an individual. In order to study the relations between communities and location clusters, we propose the index of location entropy to measure the degree of dispersion of the locations in each community, and the index of community entropy to measure the degree of dispersion of the communities in each location cluster. More importantly these two indexes can potentially help measure the influential power for the topic community and monitor the active degree of people's online social behavior in a location cluster.