NDLI: Crowd-based urban characterization: extracting crowd behavioral patterns in urban areas from Twitter

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Crowd-based urban characterization: extracting crowd behavioral patterns in urban areas from Twitter

Content Provider	ACM Digital Library
Author	Wakamiya, Shoko Sumiya, Kazutoshi Lee, Ryong
Abstract	The advent of location-based social networking sites provides an open sharing space of crowd-sourced lifelogs that can be regarded as a novel source to monitor massive crowds' lifestyles in the real world. In this paper, we challenge to analyze urban characteristics in terms of crowd behavior by utilizing the crowd lifelogs in urban area. In order to collect crowd behavioral data, we utilize Twitter where enormous numbers of geo-tagged crowd's micro lifelogs can be easily acquired. We model the crowd behavior on the social network sites as a feature, which will be used to derive crowd-based urban characteristics. Based on this crowd behavior feature, we analyze significant crowd behavioral patterns for extracting urban characteristics. In the experiment, we actually conduct the urban characterization over the crowd behavioral patterns using a large number of geo-tagged tweets found in Japan from Twitter and report a comparison result with map-based observation of cities as an evaluation.
Starting Page	77
Ending Page	84
Page Count	8
File Format	PDF
ISBN	9781450310338
DOI	10.1145/2063212.2063225
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-11-01
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Crowd behavior Urban characteristics Location-based social network sites
Content Type	Text
Resource Type	Article

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