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New Thread App Feedback
Data Science and Analytics
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Free
About
This dataset presents a collection of over 37,000 reviews for the popular New Thread mobile application, sourced from both the Google Play Store and Apple App Store. It is a meticulously curated resource designed for researchers, data scientists, and machine learning enthusiasts. The dataset facilitates in-depth analysis of user sentiments and opinions, enabling exploration of natural language processing, sentiment analysis, and app performance assessment. It provides insight into user satisfaction, usability, feature preferences, and potential areas for app improvement. Each review includes star ratings and sentiment labels, such as positive, negative, or neutral, along with essential metadata like review date and app version.
Columns
- index: A sequential identifier for each record.
- source: Indicates the platform from which the review was collected (e.g., Google Play Store, App Store).
- source (play store or app store): Specifies the broad category of the source platform.
- review_id: A unique identifier generated for each user review.
- user_name: The name of the user who submitted the review.
- review_title: A brief title provided for the review.
- review_description: The main text content of the user's review.
- rating: The star rating assigned by the user (typically from 1 to 5).
- thumbs_up: A count of validations or 'likes' provided by other users for the review.
- review_date: The date when the review was submitted.
- meta-data_1: Additional metadata related to the review, corresponding to
review_date. - developer_response: Any response provided by the app developer to the user's review.
- meta-data_2: Additional metadata related to the review, corresponding to
developer_response.
Distribution
The dataset comprises over 37,000 entities or reviews, with approximately 35,000 data points originating from the Google Play Store and about 2,000 from the Apple App Store. This distribution means around 95% of the data is from Google Play and 5% from the App Store. The data file is typically provided in a CSV format. Ratings within the dataset range from 1 to 5 stars, with a significant proportion of reviews being 5-star ratings (around 17,000 reviews). The majority of reviews have a low 'thumbs_up' count.
Usage
This dataset is ideally suited for:
- Conducting natural language processing (NLP) tasks.
- Performing sentiment analysis to understand user opinions.
- Assessing and monitoring app performance.
- Benchmarking various sentiment analysis models.
- Training machine learning algorithms for text classification or sentiment prediction.
- Exploratory data analysis to uncover patterns and trends in user feedback.
- Identifying areas for improving user experience and app features.
- Gaining valuable insights into the New Thread app's reception and evolution.
Coverage
The dataset's coverage is global, encompassing user reviews from around the world. The time range for the reviews spans from early July 2023 to early August 2023, specifically from 5th July 2023 to 7th August 2023. While it includes metadata such as reviewer demographics where available, detailed demographic breakdowns are not explicitly provided within the source material.
License
CC0
Who Can Use It
- Researchers: For academic studies on mobile app user feedback, NLP, and sentiment analysis methodologies.
- Data Scientists: To build and evaluate machine learning models for sentiment detection and predictive analytics on app reviews.
- Machine Learning Enthusiasts: For hands-on practice with real-world text data, model training, and feature engineering.
- App Developers and Product Managers: To understand user perceptions, identify bugs, gather feature requests, and guide app development based on direct user feedback.
- Marketing Analysts: To gauge public sentiment towards the app and inform marketing strategies.
Dataset Name Suggestions
- Thread App Reviews Dataset
- Mobile App User Sentiment Data
- New Thread App Feedback
- App Store Review Analysis Data
- User Opinion Threads
Attributes
Original Data Source: Thread app dataset: 37000 entities
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