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Content Mining of Microblogs.

Authors :
Cingiz, M. Ozgur
Diri, Banu
Source :
2012 IEEE/ACM International Conference on Advances in Social Networks Analysis & Mining; 1/ 1/2012, p835-838, 4p
Publication Year :
2012

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. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISBNs :
9781467324977
Database :
Complementary Index
Journal :
2012 IEEE/ACM International Conference on Advances in Social Networks Analysis & Mining
Publication Type :
Conference
Accession number :
86576254
Full Text :
https://doi.org/10.1109/ASONAM.2012.151