NDLI: Understanding urban human activity and mobility patterns using large-scale location-based data from online social media

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Understanding urban human activity and mobility patterns using large-scale location-based data from online social media

Content Provider	ACM Digital Library
Author	Ukkusuri, Satish V. Hasan, Samiul Zhan, Xianyuan
Abstract	Location-based check-in services enable individuals to share their activity-related choices providing a new source of human activity data for researchers. In this paper urban human mobility and activity patterns are analyzed using location-based data collected from social media applications (e.g. Foursquare and Twitter). We first characterize aggregate activity patterns by finding the distributions of different activity categories over a city geography and thus determine the purpose-specific activity distribution maps. We then characterize individual activity patterns by finding the timing distribution of visiting different places depending on activity category. We also explore the frequency of visiting a place with respect to the rank of the place in individual's visitation records and show interesting match with the results from other studies based on mobile phone data.
Starting Page	1
Ending Page	8
Page Count	8
File Format	PDF
ISBN	9781450323314
DOI	10.1145/2505821.2505823
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-08-11
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Urban activity pattern Large-scale Social media Human mobility pattern Location-based data
Content Type	Text
Resource Type	Article

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