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Flipkart Product Reviews and Ratings
Reviews & Ratings
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset captures customer reviews and ratings for the boAt Rockerz 400 product [1, 2]. It serves to provide insights into customer feedback regarding a specific item [1]. The data can be instrumental in sentiment analysis, allowing for the classification of reviews as either positive or negative, for example, by setting a threshold such as ratings of 4 or higher as positive and below 4 as negative [1]. Furthermore, it supports multi-class classification by treating each star rating as a distinct category [1]. This dataset facilitates various visualisations, interpretations, and the development of predictive models based on customer feedback [1].
Columns
The dataset is structured with two key columns [1, 2]:
- Review: This column contains the textual reviews provided by the customer [1, 2].
- Rating: This column represents the star ratings given by the customer [1, 2]. These ratings can be interpreted for sentiment or as individual classes for analysis [1].
Distribution
The data file is typically in a CSV format [3]. It consists of only two columns [2]. The distribution of ratings is detailed as follows [2]:
- 1.00 - 1.40: 691 counts
- 1.80 - 2.20: 310 counts
- 3.00 - 3.40: 884 counts
- 3.80 - 4.20: 2,365 counts
- 4.60 - 5.00: 5,726 counts
Usage
This dataset is ideally suited for a variety of analytical and machine learning applications [1]:
- Sentiment analysis: Determining the overall positive or negative sentiment expressed in customer reviews [1].
- Binary classification models: Creating models that classify reviews into two categories, such as 'Positive' (e.g., rating >=4) and 'Negative' (e.g., rating <4) [1].
- Multi-class classification: Developing models that predict specific star ratings as individual classes [1].
- Customer feedback analysis: Gaining insights into product performance and customer satisfaction.
- Natural Language Processing (NLP) tasks: Utilising the review text for various NLP experiments and model training [1].
Coverage
The dataset is global in its potential region of application, as indicated by its listing on a marketplace [4]. No specific time range for the reviews or detailed demographic scope is provided within the source material.
License
CCO
Who Can Use It
This dataset is valuable for a range of users interested in customer feedback and machine learning [1]:
- Data Scientists working on sentiment analysis or classification tasks.
- Machine Learning Engineers developing models for product review understanding.
- Researchers in the fields of NLP, data mining, and consumer behaviour.
- Businesses seeking to understand customer satisfaction and improve product offerings based on feedback.
Dataset Name Suggestions
- Flipkart Customer Review and Rating
- E-commerce Product Reviews and Ratings
- boAt Rockerz 400 Customer Feedback
- Customer Product Star Ratings
Attributes
Original Data Source: Flipkart Customer Review and Rating
QUALITY