Dark Mode
Dating App Sentiment Analysis Dataset
Reviews & Ratings
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset provides a collection of user reviews and ratings for dating applications, primarily sourced from the Google Play Store for the Indian region between 2017 and 2022. It offers valuable insights into user sentiment, evolving trends, and common feedback regarding dating apps. The data is particularly useful for practising Natural Language Processing (NLP) tasks such as sentiment analysis, topic modelling, and identifying user concerns.
Columns
- Index: A unique identifier for each review entry.
- Name: The name of the user who left the review.
- Username: The username of the reviewer.
- Review: The textual content of the review left by the user.
- Rating: The numerical rating given by the user to the app, indicating their satisfaction level.
- #ThumbsUp: A measure of how useful the review was perceived to be by other users.
- Date&Time: The specific date and time when the review was posted.
- App: The name of the dating application being reviewed.
- Label Count: A numerical label, the specific purpose of which is not detailed in the provided information, but it appears to relate to ranges of index or other numerical values within the dataset.
Distribution
The dataset is typically provided in a CSV file format. It contains a substantial number of records, estimated to be around 527,000 individual reviews. This makes it suitable for large-scale data analysis and machine learning projects. The dataset structure is tabular, with clearly defined columns for review content, metadata, and user feedback. Specific row/record counts are not exact but are indicated by the extensive range of index labels.
Usage
This dataset is ideally suited for a variety of analytical and machine learning applications:
- Analysing trends in dating app usage and perception over the years.
- Determining which dating applications receive more favourable responses and if this consistency has changed over time.
- Identifying common issues reported by users who give low ratings (below 3/5).
- Investigating the correlation between user enthusiasm and their app ratings.
- Performing sentiment analysis on review texts to gauge overall user sentiment.
- Developing Natural Language Processing (NLP) models for text classification, entity recognition, or summarisation.
- Examining the perceived usefulness of top-rated reviews.
- Understanding user behaviour and preferences across different dating apps.
Coverage
The dataset primarily covers user reviews from the Google Play Store, specifically for the Indian country region ('in'), despite being titled as "all regions" in some contexts. The data spans a time range from 2017 to 2022, offering a multi-year perspective on dating app trends and user feedback. There are no specific demographic details for the reviewers themselves beyond their reviews and ratings.
License
CCO
Who Can Use It
This dataset is suitable for:
- Data Scientists and Analysts: For conducting deep dives into user sentiment, trend analysis, and predictive modelling.
- NLP Practitioners and Researchers: As a practical dataset for training and evaluating natural language processing models, especially for text classification and sentiment analysis tasks.
- App Developers and Product Managers: To understand user feedback, identify areas for improvement in their own or competing dating applications, and inform product development strategies.
- Market Researchers: To gain insights into the consumer behaviour and preferences within the online dating market.
- Students and Beginners: It is tagged as 'Beginner' friendly, making it a good resource for those new to data analysis or NLP projects.
Dataset Name Suggestions
- Google Play Dating App Reviews (India, 2017-2022)
- Indian Dating App User Reviews
- Mobile Dating App Reviews & Ratings
- Dating App Sentiment Analysis Dataset
- Google Play Dating App Feedback
Attributes
Original Data Source: Dating Apps Reviews 2017-2022 (all regions)
QUALITY