A hybrid approach to sentiment analysis
Published 1 July 2016Open access
Orestes Appel, Francisco Chiclana, Jenny Carter, Hamido Fujita
Citations29
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TL;DR
This contribution presents a hybrid approach to Sentiment Analysis encompassing the use of semantic rules, fuzzy sets, unsupervised machine learning techniques and a sentiment lexicon improved with the support of Senti-WordNet.
Abstract
This contribution presents a hybrid approach to Sentiment Analysis (SA) encompassing the use of semantic rules, fuzzy sets, unsupervised machine learning techniques and a sentiment lexicon improved with the support of Senti-WordNet. A Hybrid Standard Classification is first carried out, which is further enhanced into a Hybrid Advanced approach incorporating linguistic classification of semantic polarity modelled using fuzzy sets. The mechanism of the new SA methodology is illustrated by applying it to compute the polarity of a given sentence and to a benchmarking publicly available dataset: the Movie Review Dataset.
Keywords
Computer Science
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