GI-LYS - Artigos: Envíos recentes
Mostrando ítems 6-10 de 43
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A syntactic approach for opinion mining on Spanish reviews
(Cambridge University Press, 2015-01)[Abstract]: We describe an opinion mining system which classifies the polarity of Spanish texts. We propose an NLP approach that undertakes pre-processing, tokenisation and POS tagging of texts to then obtain the syntactic ... -
A linguistic approach for determining the topics of Spanish Twitter messages
(SAGE Publications & CILIP, 2015)[Abstract]: The vast number of opinions and reviews provided in Twitter is helpful in order to make interesting findings about a given industry, but given the huge number of messages published every day, it is important ... -
On the usefulness of lexical and syntactic processing in polarity classification of Twitter messages
(Wiley, 2015-09)[Abstract]: Millions of micro texts are published every day on Twitter. Identifying the sentiment present in them can be helpful for measuring the frame of mind of the public, their satisfaction with respect to a product, ... -
Universal, unsupervised (rule-based), uncovered sentiment analysis
(Elsevier, 2017-02)[Abstract]: We present a novel unsupervised approach for multilingual sentiment analysis driven by compositional syntax-based rules. On the one hand, we exploit some of the main advantages of unsupervised algorithms: (1) ... -
Supervised sentiment analysis in multilingual environments
(Elsevier, 2017-05)[Abstract]: This article tackles the problem of performing multilingual polarity classification on Twitter, comparing three techniques: (1) a multilingual model trained on a multilingual dataset, obtained by fusing existing ...