Fuzzy Based Sentiment Classification Using Fuzzy Linguistic Hedges for Decision Making
DOI:
https://doi.org/10.12723/mjs.sp2.4Keywords:
Fuzzy linguistic hedges, text classification, sentiment analysis, pre-processingAbstract
Sentiment analysis is used to identify the attitude, opinions, and emotions of people towards a certain topic or entity. The goal of this paper is to develop a model to do sentiment classification of online product reviews using fuzzy linguistic hedges. The proposed model will be trained on a corpus of reviews, and will be able to classify reviews into a number of sentiment categories, such as positive, neutral, and negative. The proposed model will use fuzzy linguistic hedges to improve the accuracy of the sentiment analysis. The fuzzy linguistic hedges will be used to add context and nuance to the sentiment analysis, and will enable the model to better distinguish between subtle differences in sentiment. The proposed model is tested with microblog electronics dataset. The proposed model is used for making decisions.
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