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E-commerce Product Reviews & Sentiment
Reviews & Ratings
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset provides a focused collection of customer reviews and ratings, originally extracted from the Amazon Megazine Reviews dataset. It was gathered in 2023 by McAuley Lab and is specifically designed for sentiment analysis tasks. A unique sentiment feature has been added, categorising review sentiments as negative, neutral, or positive, derived from the original 1-5 star ratings. This resource is valuable for understanding customer feedback and developing sentiment models.
Columns
- text: This column contains the verbatim review text provided by the customer [1, 2].
- rating: A numerical rating given by the reviewer for the product, presented on a scale of 1 to 5 [1, 2].
- sentiment: An extracted sentiment score for each review. This feature is scaled from 0 to 2, where 0 represents a negative sentiment, 1 indicates a neutral sentiment, and 2 denotes a positive sentiment [1, 2].
Distribution
The dataset is typically provided in a CSV file format [3]. While the exact total number of rows or records is not explicitly stated, label counts for ratings and sentiments suggest it contains a substantial volume of data points, with thousands of unique values and tens of thousands of records for analysis [2].
Usage
This dataset is ideally suited for various analytical and machine learning applications. Primary uses include performing sentiment analysis tasks, developing natural language processing (NLP) models, and engaging in text classification. It can also be applied in e-commerce settings to gain insights from customer feedback [1].
Coverage
The data was collected in 2023 [1] and has a global regional scope [4]. Specific demographic details of the reviewers are not detailed in the provided information.
License
CC-BY
Who Can Use It
This dataset is beneficial for data scientists, machine learning engineers, and researchers focused on text analytics and sentiment modelling. It is also highly relevant for businesses within the e-commerce sector looking to analyse customer reviews, assess product performance, and enhance customer satisfaction based on textual feedback.
Dataset Name Suggestions
- Amazon Magazine Review Sentiment 2023
- E-commerce Product Reviews & Sentiment
- McAuley Lab Amazon Textual Feedback
Attributes
Original Data Source: Amazon Megazine Reviews dataset'23
QUALITY