Title :
Content Mining of Microblogs
Author :
Cingiz, M. Ozgur ; Diri, B.
Author_Institution :
Comput. Eng. Dept., Yildiz Tech. Univ., Istanbul, Turkey
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;
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
DOI :
10.1109/ASONAM.2012.151