AN OVERVIEW OF SENTIMENT POLARITY AND SUBJECTIVITY DETECTION IN TEXT ALONG EMPIRICAL TESTING
Keywords:sentiment, polarity, subjectivity, detection, synonym, semantics
Sentiment analysis start through lexicon and corpuses in which words keep semantic orientation called polarity. The level of positivity or negativity in a text is referred to as its polarity. In the current era, detection patterns have been viewed as a bright career in research. The reason behind that is rapid growth in online textual data day by day. Turn over toward at the present; the focus is polarity detection according to the subjectivity while subjectivity remains multiple directions. As a result, an intrinsic relationship is considered between them. Subjectivity detection performs prevention about sentiment classifier. Sentiment analysis through MC dataset along experimental testing provides the better results. This article argues on the difference between polarity and subjectivity detection among subjectivity terms. Many state-of-the-art algorithms talk about their important features. For sentiment polarity detection, SentiWordNet used utmost for training in which terms organized in the set of synonyms. Comparison between supervised and semi-supervised approaches is also displayed in detail.
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