Mining human mobility patterns from social geo-tagged data

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• 作者：Carmela Comito^a ; ^{comito@icar.cnr.it} ; Deborah Falcone^b ; ^{dfalcone@dimes.unical.it} ; Domenico Talia^b ; ^{talia@dimes.unical.it}
• 关键词：Trajectory pattern mining ; Geo-social data ; Human mobility
• 刊名：Pervasive and Mobile Computing
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：33
• 期：Complete
• 页码：91-107
• 全文大小：2117 K
• 卷排序：33

文摘

Online social networks allow users to tag their posts with geographical coordinates collected through the GPS interface of smart phones. The time- and geo-coordinates associated with a sequence of posts/tweets manifest the spatial–temporal movements of people in real life. This paper aims to analyze such movements to discover people and community behavior. To this end, we defined and implemented a novel methodology to mine popular travel routes from geo-tagged posts. Our approach infers interesting locations and frequent travel sequences among these locations in a given geo-spatial region, as shown from the detailed analysis of the collected geo-tagged data.