DocumentCode
3156402
Title
Content Mining of Microblogs
Author
Cingiz, M. Ozgur ; Diri, B.
Author_Institution
Comput. Eng. Dept., Yildiz Tech. Univ., Istanbul, Turkey
fYear
2012
fDate
26-29 Aug. 2012
Firstpage
835
Lastpage
838
Abstract
Emergence of Web 2.0, internet users can share their contents with other users using social networks. In this paper microbloggers´ contents are evaluated with respect to how they reflect their categories. Migrobloggers´ category information, which is one of the four categories that are economy sport, entertainment or technology, is taken from wefollow.com application. 2105 RSS news feeds, whose category labels are same with microbloggers´ contributions, are used as training data for classification. In this study two types of users´ contributions are taken as test data. These users are normal micro loggers and bots. Classification results show that bots provide more categorical content than normal users.
Keywords
Internet; content management; data mining; pattern classification; social networking (online); 2105 RSS news feeds; Internet users; Web 2.0; classification; content mining; economy sport; entertainment; microblogs; migroblogger category information; social networks; technology; training data; wefollow.com application; Educational institutions; Entertainment industry; Feeds; Support vector machine classification; Text categorization; Training; classification; content mining; data mining; microblogging; social web mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on
Conference_Location
Istanbul
Print_ISBN
978-1-4673-2497-7
Type
conf
DOI
10.1109/ASONAM.2012.151
Filename
6425656
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