Abstract
Sentiment Analysis is an active area of research and has presented promising results. There are several approaches for modeling that are capable of performing classifications with good accuracy. However, there is no approach that performs well in all contexts, and the nature of the corpus used can exert a great influence. This paper describes a research that presents a convolutional neural network approach to the Sentiment Analysis Applied to Hotel’s Reviews, and performs a comparison with models previously executed on the same corpus.
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This research is supported in part by the funding agencies FAPEMIG, CNPq, and CAPES.
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de Souza, J.G.R., de Paiva Oliveira, A., de Andrade, G.C., Moreira, A. (2018). A Deep Learning Approach for Sentiment Analysis Applied to Hotel’s Reviews. In: Silberztein, M., Atigui, F., Kornyshova, E., Métais, E., Meziane, F. (eds) Natural Language Processing and Information Systems. NLDB 2018. Lecture Notes in Computer Science(), vol 10859. Springer, Cham. https://doi.org/10.1007/978-3-319-91947-8_5
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DOI: https://doi.org/10.1007/978-3-319-91947-8_5
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