Abstract
The paper concerns analysis of social groups in blogosphere using text mining methods to discover additional knowledge about groups and users. Two methods to distinguish messages (the first one - between messages from main and secondary thread, the second one - between facts and opinions) in blogosphere were proposed and their quality was assessed on manually annotated dataset. Both tasks are very important and proposed methods deal with them in a fully automatic way. The results were obtained on real-world data from Polish blogosphere.
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Gliwa, B., Zygmunt, A., Koźlak, J., Cetnarowicz, K. (2014). Application of Text Mining to Analysis of Social Groups in Blogosphere. In: Contucci, P., Menezes, R., Omicini, A., Poncela-Casasnovas, J. (eds) Complex Networks V. Studies in Computational Intelligence, vol 549. Springer, Cham. https://doi.org/10.1007/978-3-319-05401-8_27
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DOI: https://doi.org/10.1007/978-3-319-05401-8_27
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-05400-1
Online ISBN: 978-3-319-05401-8
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