Abstract
We present a methodology for automatically enlarging a Portuguese sentiment lexicon for mining social judgments from text, i.e., detecting opinions on human entities. Starting from publicly-availabe language resources, the identification of human adjectives is performed through the combination of a linguistic-based strategy, for extracting human adjective candidates from corpora, and machine learning for filtering the human adjectives from the candidate list. We then create a graph of the synonymic relations among the human adjectives, which is built from multiple open thesauri. The graph provides distance features for training a model for polarity assignment. Our initial evaluation shows that this method produces results at least as good as the best that have been reported for this task.
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Silva, M.J., Carvalho, P., Sarmento, L. (2012). Building a Sentiment Lexicon for Social Judgement Mining. In: Caseli, H., Villavicencio, A., Teixeira, A., Perdigão, F. (eds) Computational Processing of the Portuguese Language. PROPOR 2012. Lecture Notes in Computer Science(), vol 7243. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28885-2_25
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DOI: https://doi.org/10.1007/978-3-642-28885-2_25
Publisher Name: Springer, Berlin, Heidelberg
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