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Abraham, Thomas
- Sentimental Analysis using Product Review Data
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Authors
Affiliations
1 Assistant Professor, Sharda University, Greater Noida, Uttar Pradesh,, IN
2 Assistant Professor, Sharda University, Uttar Pradesh, Greater Noida,, IN
3 Student, Sharda University, Greater Noida, Uttar Pradesh,, IN
4 Sharda University, Greater Noida, Uttar Pradesh,, IN
1 Assistant Professor, Sharda University, Greater Noida, Uttar Pradesh,, IN
2 Assistant Professor, Sharda University, Uttar Pradesh, Greater Noida,, IN
3 Student, Sharda University, Greater Noida, Uttar Pradesh,, IN
4 Sharda University, Greater Noida, Uttar Pradesh,, IN
Source
Telecom Business Review, Vol 15, No 1 (2022), Pagination: 11-16Abstract
Our work systematically analyze the sentiment of product reviews and evaluate the correlation with their corresponding ratings.Sentiment analysis identifies the positive or negative mood represented in a piece of literature. Consumers write reviews withprecise ratings on e-commerce platforms such as Amazon. We’ve noticed that there are occasionally discrepancies between thereview and the rating. We performed deep learning guided sentiment analysis to identify such mismatches from amazon productreview data. We convert reviews to vectors using paragraph vector and use them to develop a neural network using a GRU orgated recurrent unit our perspective makes advantage of both the semantic link between review content and product information.Keywords
Sentiment Analysis, RNN, SVM, GRU.
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