Evaluating EmotiBlog robustness for sentiment analysis tasks

Authors:
Javi Fernández;Ester Boldrini;José Manuel Gómez;Patricio Martínez-Barco
Affiliations:
University of Alicante, GPLSI, Department of Language and Computying Systems, Spain;University of Alicante, GPLSI, Department of Language and Computying Systems, Spain;University of Alicante, GPLSI, Department of Language and Computying Systems, Spain;University of Alicante, GPLSI, Department of Language and Computying Systems, Spain
Venue:
NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
Year:
2011

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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.