NDLI: Discovery of user behavior patterns from geo-tagged micro-blogs

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Discovery of user behavior patterns from geo-tagged micro-blogs

Content Provider	ACM Digital Library
Author	Sumiya, Kazutoshi Fujisaka, Tatsuya Lee, Ryong
Abstract	The explosive growth of micro-blogging sites such as Twitter has enabled folks to share their personal up-to-dates. Compared to conventional blog sites, through the short length of messages, micro-blogging sites help users easily express their experiences, thoughts and feelings and share them instantly and globally. In addition, mobile devices based micro-blogging applications are ensuring the usefulness in a variety of our daily activities without spatial or temporal restriction. Especially, the most significant characteristics chiefly possible in such mobile micro-blogging is on the fact that the cutting-edge smartphones can utilize location sensing information that make it clear to analyze where the published messages are made almost in real time. In the respect of the diversity and the quantity of crowds writing the micro-blogs, we are sure that the micro-blogging sites can be a very important social media platform where a lot of valuable knowledge such as geographic social phenomena can be extracted. In this paper, we endeavor to find geographic social patterns from user movement histories made by mass mobile micro-bloggers. We particularly propose fundamental models based on aggregation and dispersion about movements of micro-bloggers in geographic regions. We also performed experiments to discover geographic characteristics from the micro-blog data actually gathered from Twitter.
Starting Page	1
Ending Page	10
Page Count	10
File Format	PDF
ISBN	9781605588933
DOI	10.1145/2108616.2108660
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-01-14
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	User behavior patterns Micro-blog
Content Type	Text
Resource Type	Article

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