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.
Appel, O., Chiclana, F., Carter, J., & Fujita, H. (2016). A Hybrid Approach to the Sentiment Analysis Problem at the Sentence Level. Knowledge-Based Systems, 108, 110-124. https://doi.org/10.1016/j.knosys.2016.05.040