Pattern Based Multi Class Sentiment Analysis

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Sentiment analysis and opinion mining in social networks present nowadays a hot topic of research. However, most of the state of the art works and researches on the automatic sentiment analysis and opinion mining of texts collected from social networks and microblogging websites are oriented toward the binary classification (i.e., classification into “positive”and “negative”) or the ternary classification (i.e., classification into “positive,”“negative,”and “neutral”) of texts. In this paper, we propose a novel approach that, in addition to the aforementioned tasks of  binary and ternary classifications, goes deeper in the classification of texts collected from Twitter and classifies these texts into multiple sentiment classes. While in this paper, we limit our scope to approx ten different sentiment classes.

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