Abdullah Muhammad, Salwani Abdullah, Nor Samsiah Sani*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1783-1799, 2021, DOI:10.32604/cmc.2021.018593
Abstract Feature selection and sentiment analysis are two common studies that are currently being conducted; consistent with the advancements in computing and growing the use of social media. High dimensional or large feature sets is a key issue in sentiment analysis as it can decrease the accuracy of sentiment classification and make it difficult to obtain the optimal subset of the features. Furthermore, most reviews from social media carry a lot of noise and irrelevant information. Therefore, this study proposes a new text-feature selection method that uses a combination of rough set theory (RST) and teaching-learning based optimization (TLBO), which is… More >
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