Abstract
: Commenting on social media about any product, person or event has become a common practice in current trend. This opinion yields and also predicts the reputation about the particular element. So, it is considered most important to detect the exact wavelength of the reviews passed in the social media. This paper aims to facilitate the domain-based sentiment detection by enhancing the existing sentiment lexicon. After enhancing it has attained increased accuracy of 85.1% than the existing lexicon in classifying the positive and negative reviews with fine-tuned pre-processing techniques. And also, the BoW detection has been improved than the existing lexicon. The online course reviews are considered for sentiment polarity detection.
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