Dark Mode
ChatGPT App Sentiment Analysis Collection
Product Reviews & Feedback
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
Unveiling User Perspectives: Analysing Experiences and Feedback
This data offers crucial insights into user experiences and feedback concerning the ChatGPT application. The collection contains 2,292 individual reviews, providing a valuable resource for understanding user satisfaction levels and potential areas for product improvement within the ChatGPT app. The data is pre-labelled for sentiment analysis tasks, ensuring a ready-to-use resource for machine learning applications. The collection provides a balanced view of user opinions.
Columns
- Review: Contains the raw text of the user feedback. Of the total records, 2,249 entries are valid (98%), with 43 instances noted as missing (2%). This column is the primary input for text processing tasks.
- label: Represents the sentiment assigned to the review, categorized as either POSITIVE or NEGATIVE. All 2,292 records are validated and labelled (100%).
Distribution
The resource is delivered as a CHATGPT.csv file, with a size of approximately 503.12 kB. It consists of 2,292 distinct user reviews across two columns. The sentiment distribution provides a view of opinions: 55% of the reviews (1,264 records) are classified as NEGATIVE, and 45% (1,028 records) are classified as POSITIVE. The overall usability rating for this resource is 10.00.
Usage
This collection is ideal for various natural language processing applications, including text classification and training predictive models. Specific applications include:
- Developing robust sentiment analysis models.
- Benchmarking text pre-processing techniques.
- Performing detailed user feedback analysis to gauge satisfaction.
- Studying trends in user acceptance of artificial intelligence applications.
Coverage
The scope is strictly limited to user feedback concerning the ChatGPT application. The data is a static resource; the expected update frequency is Never. No specific geographical or demographic attributes related to the reviewers are detailed within the data structure.
License
Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
Who Can Use It
- Machine Learning Engineers: For building models focused on sentiment detection.
- Data Scientists: For exploratory data analysis and developing insights into user language patterns.
- Product Development Teams: For targeted analysis of negative feedback to inform product improvement strategies.
- Academic Researchers: For studying human-computer interaction and public perception of LLMs.
Dataset Name Suggestions
- ChatGPT App Sentiment Analysis Collection
- User Feedback Sentiment for ChatGPT Reviews (2k+)
- Text Classification Dataset: ChatGPT Reviews
Attributes
Original Data Source: ChatGPT App Sentiment Analysis Collection
QUALITYLoading...