{"title":"Understanding the Regularity and Variability of Human Mobility from Geo-trajectory","authors":"Yunji Liang, Xingshe Zhou, Bin Guo, Zhiwen Yu","doi":"10.1109/WI-IAT.2012.163","DOIUrl":null,"url":null,"abstract":"Over the last few years, many efforts have been devoted to revealing human mobility patterns. However, the regularity and variability of human mobility from a microscopic view, i.e., what factors affect human mobility patterns, has yet not been investigated. In this paper, we aim to study the impact factors that may affect the regularity and variability of human mobility patterns using social network analysis. Specifically, we introduce the spatial interaction matrix to represent the interaction strength and interaction semantics among spatial regions. Based on the spatial interaction matrix, we investigate the factors that impact the mobility patterns, including temporal factors, occupational factors and age factors. Our experimental results demonstrate that lots of factors such as environmental, temporal and age factors contribute to the shape of human mobility patterns.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI-IAT.2012.163","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Over the last few years, many efforts have been devoted to revealing human mobility patterns. However, the regularity and variability of human mobility from a microscopic view, i.e., what factors affect human mobility patterns, has yet not been investigated. In this paper, we aim to study the impact factors that may affect the regularity and variability of human mobility patterns using social network analysis. Specifically, we introduce the spatial interaction matrix to represent the interaction strength and interaction semantics among spatial regions. Based on the spatial interaction matrix, we investigate the factors that impact the mobility patterns, including temporal factors, occupational factors and age factors. Our experimental results demonstrate that lots of factors such as environmental, temporal and age factors contribute to the shape of human mobility patterns.