Abstract
EmotiBlog is a corpus labelled with the homonymous annotation schema designed for detecting subjectivity in the new textual genres. Preliminary research demonstrated its relevance as a Machine Learning resource to detect opinionated data. In this paper we compare EmotiBlog with the JRC corpus in order to check the EmotiBlog robustness of annotation. For this research we concentrate on its coarse-grained labels. We carry out a deep ML experimentation also with the inclusion of lexical resources. The results obtained show a similarity with the ones obtained with the JRC demonstrating the EmotiBlog validity as a resource for the SA task.
This work has been partially founded by the TEXTMESS 2.0 (TIN2009-13391-C04-01) and Prometeo (PROMETEO/2009/199) projects and also by the complimentary action from the Generalitat valenciana (ACOMP/2011/001).
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Fernández, J., Boldrini, E., Gómez, J.M., Martínez-Barco, P. (2011). Evaluating EmotiBlog Robustness for Sentiment Analysis Tasks. In: Muñoz, R., Montoyo, A., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2011. Lecture Notes in Computer Science, vol 6716. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22327-3_41
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DOI: https://doi.org/10.1007/978-3-642-22327-3_41
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