Determining product ratings and ranking product reviews for e-commerce platforms.
One of the most critical challenges in e-commerce is accurately calculating the ratings given to products after purchase. Solving this issue enhances customer satisfaction for e-commerce sites, helps products stand out for sellers, and ensures a seamless shopping experience for buyers. Another key challenge is the proper ranking of product reviews. Misleading reviews can impact sales directly, resulting in financial losses and customer dissatisfaction. Addressing these two core problems helps e-commerce platforms and sellers increase sales while providing customers with a smooth purchasing journey.
This dataset, containing Amazon product data, includes various metadata related to product categories. It specifically covers user ratings and reviews for the most-reviewed product in the electronics category.
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reviewerID: User ID
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asin: Product ID
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reviewerName: User Name
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helpful: Helpfulness rating (upvotes)
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reviewText: Review content
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overall: Product rating
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summary: Review summary
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unixReviewTime: Review time (Unix format)
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reviewTime: Raw review time
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day_diff: Number of days since the review
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helpful_yes: Number of helpful votes
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total_vote: Total number of votes for the review
** In this study, Miuul educational resources were used as a reference.