2022 |
Volume 15 |
Issue Issue 1
Sentimental Analysis using Product Review Data
1.
Amit Kumar
– Sharda University, Greater Noida, Uttar Pradesh, India.
2.
Sonia Setia
– Sharda University, Greater Noida, Uttar Pradesh, India.
3.
Arjun Singh
– Sharda University, Greater Noida, Uttar Pradesh, India.
4.
Thomas Abraham
– Sharda University, Greater Noida, Uttar Pradesh, India.
5.
Yashaswi Shakya
– Sharda University, Greater Noida, Uttar Pradesh, India.
Received
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Accepted
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Published
12-Sep-2022
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Abstract
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 with
precise ratings on e-commerce platforms such as Amazon. We’ve noticed that there are occasionally discrepancies between the
review and the rating. We performed deep learning guided sentiment analysis to identify such mismatches from amazon product
review data. We convert reviews to vectors using paragraph vector and use them to develop a neural network using a GRU or
gated 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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