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Whatssap App Ratings & Feedback
Reviews & Ratings
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset provides a continuously updated collection of user-generated reviews and ratings for the Whatssap Android App. It serves as a rich source of user feedback, including details on the relevance of reviews and their submission dates. The data is updated daily, offering an up-to-date view of user sentiment and app performance.
Columns
The dataset includes the following columns:
- reviewId: A unique identifier for each review.
- id: An identifier, potentially similar to reviewId or specific to the platform.
- userName: The name of the user who submitted the review.
- reviewer: Details about the reviewer, possibly an alias or a generic user type.
- content: The full text of the user's review.
- review: Similar to content, representing the user's written feedback.
- score: The numerical score or rating given by the user, ranging from 1 to 5.
- rating: Another representation of the numerical score.
- thumbsUpCount: The number of 'likes' or 'thumbs up' received by the review.
- likes: Similar to thumbsUpCount, indicating positive feedback on the review.
- reviewCreatedVersion: The version of the app when the review was created.
- app version: The version of the app.
- at: The specific date and time when the review was shared.
- date of review: Similar to 'at', indicating the date the review was posted.
Distribution
The dataset is typically provided as a CSV file. It is a continually updated dataset, with new information added on a daily basis. The dataset contains over one million records, as indicated by the substantial counts across various review scores and thumbs-up counts. For instance, over 700,000 reviews have a rating of 4.92-5.00, and over a million reviews have a thumbsUpCount between 0 and 4632.02. The data spans a significant time range, with records from August 2014 up to July 2025.
Usage
This dataset is ideal for various analytical purposes, including:
- Sentiment analysis: Understanding user opinions and emotional tone towards the Whatssap App.
- App performance monitoring: Tracking user satisfaction and identifying trends over time.
- User feedback analysis: Gaining insights into feature requests, bug reports, and overall user experience.
- Natural Language Processing (NLP): Training and evaluating NLP models for text classification, entity recognition, and opinion mining related to app reviews.
- Market research: Analysing user preferences and competitive landscapes in the mobile app market.
Coverage
The dataset offers global coverage of user reviews. The time range of the data extends from August 2014 to July 2025, indicating a long-term collection effort. The data is updated daily, ensuring current insights into user feedback. There are no specific notes on data availability for certain demographic groups.
License
CC-BY-NC
Who Can Use It
This dataset is suitable for:
- Data Analysts: For trend analysis, sentiment analysis, and reporting on user feedback.
- App Developers: To identify areas for improvement, track feature adoption, and understand user pain points.
- Market Researchers: To gauge market sentiment, conduct competitive analysis, and identify emerging trends in mobile app usage.
- Data Scientists & NLP Engineers: For building and refining models related to text analysis, opinion mining, and user behaviour prediction.
Dataset Name Suggestions
- Whatssap Daily User Reviews
- Whatssap App Ratings & Feedback
- Whatssap Global User Sentiment
- Daily Whatssap App Analytics
- Whatssap Customer Feedback Archive
Attributes
Original Data Source: Whatssap Reviews [DAILY UPDATED]
QUALITY