Amazon Customer Reviews With Sentiment
Extracting Insights from Product Ratings
@kaggle.thedevastator_amazon_customer_reviews_with_2013_2019_sentiment
Extracting Insights from Product Ratings
@kaggle.thedevastator_amazon_customer_reviews_with_2013_2019_sentiment
By [source]
This dataset contains an expansive collection of Amazon customer reviews ranging from 2013 to 2019 found across various categories of products, such as smartphones, laptops, books, and refrigerators. Each customer has their own unique ID, accompanied by a review header containing the title of their review as well as a detailed description and overall rating given by the customer according to their experience. Moreover, we have included our own sentiment analysis providing an additional layer to these reviews - breaking them down into ratings for positive or negative sentiment. With our invaluable insights into customers thoughts and feelings about different products across various categories over 6 years of reviews - this dataset is valuable resource for anyone interested in discovering trends on Amazon's customer base
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If you use this dataset in your research, please credit the original authors.
Data Source
License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.
File: Amazon Review Data Web Scrapping - Amazon Review Data Web Scrapping.csv
| Column name | Description |
|---|---|
| Category | The product category of the review. (String) |
| Review_Header | The title of the customer review. (String) |
| Review_text | The detailed text of the customer review. (String) |
| Rating | The customer rating of the product. (Integer) |
| Own_Rating | The sentiment analysis rating of the customer review. (Integer) |
If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .
CREATE TABLE amazon_review_web_scrapping_amazon_review_web_scrapping (
"unique_id" BIGINT,
"category" VARCHAR,
"review_header" VARCHAR,
"review_text" VARCHAR,
"rating" BIGINT,
"own_rating" VARCHAR
);Anyone who has the link will be able to view this.