Abstract
Opinions, in news media platforms, provide a world wide access to what people think about daily life topics. Thus, exploiting such a source of information to identify the trends can be very useful in many scenarios, such as political parties who are interested in monitoring their impact. In this paper, we present an unsupervised technique to classify users based on their political orientations. Our approach is based on two main concepts: (1) the selection of the aspects and the sentiments users have expressed in their opinions, and (2) the creation of knowledge base from Wikipedia to automatically classify users according to their political orientations. We have tested our approach on two datasets crawled from CNN and Aljazeera. The results show that our approach achieves high quality results.
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Meguebli, Y., Kacimi, M., Doan, BL., Popineau, F. (2014). Unsupervised Approach for Identifying Users’ Political Orientations. In: de Rijke, M., et al. Advances in Information Retrieval. ECIR 2014. Lecture Notes in Computer Science, vol 8416. Springer, Cham. https://doi.org/10.1007/978-3-319-06028-6_49
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DOI: https://doi.org/10.1007/978-3-319-06028-6_49
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06027-9
Online ISBN: 978-3-319-06028-6
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