AMAZON PRODUCT REVIEW RATING PREDICTION WITH CONVOLUTIONAL NEURAL NETWORK (CNN)
Sentiment analysis is the application of Natural Language Processing (NLP) to determine the sentiments of texts expressed by humans. One application of sentiment analysis that is popular in the e-commerce sector is sentiment classification. Sentiment classification is used to categorize customer rev...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/74370 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Sentiment analysis is the application of Natural Language Processing (NLP) to determine the sentiments of texts expressed by humans. One application of sentiment analysis that is popular in the e-commerce sector is sentiment classification. Sentiment classification is used to categorize customer reviews of a product into positive reviews or negative reviews. The rating of the review is represented by a likert scale from 1 to 5. The Convolutional Neural Network (CNN) model is a deep learning model that can be used to clasify sentiments based on the effect of multiple pairwise words. This study aims to analyze the application of the CNN model in predicting ratings from product reviews on Amazon. Result showed that the CNN model could predict review’s ratings by 0.33 out of 1.0 F1 score and parameters that give the huge effect on CNN model are the number of filters, activation function, and also optimization algorithm for optimizing CNN parameters. |
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