Experiments on Hybrid Corpus-Based Sentiment Lexicon Acquisition (CROSBI ID 586883)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Glavaš, Goran ; Šnajder, Jan ; Dalbelo Bašić, Bojana
engleski
Experiments on Hybrid Corpus-Based Sentiment Lexicon Acquisition
Numerous sentiment analysis applications make usage of a sentiment lexicon. In this paper we present experiments on hybrid sentiment lexicon acquisition. The approach is corpus-based and thus suitable for languages lacking general dictionarybased resources. The approach is a hybrid two-step process that combines semisupervised graph-based algorithms and supervised models. We evaluate the performance on three tasks that capture different aspects of a sentiment lexicon: polarity ranking task, polarity regression task, and sentiment classification task. Extensive evaluation shows that the results are comparable to those of a well-known sentiment lexicon SentiWordNet on the polarity ranking task. On the sentiment classification task, the results are also comparable to SentiWordNet when restricted to monosentimous (all senses carry the same sentiment) words. This is satisfactory, given the absence of explicit semantic relations between words in the corpus.
sentiment lexicon; hybrid; corpus-based
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Podaci o prilogu
1-9.
2012.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the Workshop on Innovative Hybrid Approaches to Processing Textual Data, 13th Conference of the European Chapter of the Association for Computational Linguistics
Avignon: EACL
Podaci o skupu
13th Conference of the European Chapter of the Association for computational Linguistics
predavanje
23.04.2012-27.04.2012
Avignon, Francuska