Improving sentiment analysis with Part-of-Speech weighting

Sentiment Analysis is concerned with classifying the opinions in a piece of text. We present a term weighting scheme which takes into account Part-of-Speech categories to improve machine learning-based classification of sentiment in product reviews. We experimentally find optimal strengths for each Part-of-Speech category and show that using this weighting method improves overall sentiment classification.

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