The State Art of Text Sentiment from Opinions to Emotion Mining


Nor Anis Asma Sulaiman*, Leelavathi Rajamanickam
Faculty of Engineering and Built Environment & IT, SEGi University

Journal of Engineering & Technological Advances
Vol. 5, Issue 2, pp. 43-52 (2020)

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This study is aiming to analyse the feelings expressed by the users in a text on a comment posted on social media. Text Mining and Emotion Mining can be analysed by using both technique of Natural Processing Language (NLP). Mostly on the previous study of text mining is using unsupervised technique and referring to Ekman’s Emotion Model (EEM) but it has restrained coverage of polarity shifters, negations and lack emoticon. In this study have proposed a Naïve Bayes algorithm as a tool to produce users’ emotion pattern. The most important contribution of this study is to visualize the emotion’s theory with the text sentiment based on the computational methods for classifying users’ feelings from natural language text. Then, the general system framework of extracting opinions to emotion mining has produced and capable use in any domains.


Emotion, Text, Sentiment, Naïve Bayes.