ChatGPT was the chatbot that kickstarted the generative AI revolution, which has been responsible for hundreds of billions of dollars in data centres, graphics chips and AI startups. Launched by...

As of August 2025, there were 557 million monthly active users of the ChatGPT mobile application on both Android and iOS operating systems worldwide, indicating a 600 percent increase from August 2023. ChatGPT, alongside other generative AI apps, has gained significant interest in recent periods, with the app even toppling TikTok's dominance among the most downloaded mobile apps globally.

Annual users of ChatGPT worldwide are expected to grown considerably in the coming months. In 2022, around 57 million people used ChatGPT, with this number increasing to roughly 100 million by January 2023.

Dataset Description

This dataset consists of daily-updated user reviews and ratings for the ChatGPT Android App. The dataset includes several key attributes that capture various aspects of the reviews, providing insights into user experiences and feedback over time.

Columns Explanation

• userName: The display name of the user who posted the review.
• content: The text content of the review. This column contains the actual review text written by the user. It includes user opinions, feedback, and detailed descriptions of their experiences with the ChatGPT app.
• score: The rating given by the user, typically ranging from 1 to 5. This column captures the numerical rating provided by the user. Higher scores indicate better experiences, while lower scores indicate dissatisfaction.
• thumbsUpCount: The number of thumbs up (likes) the review received. This column shows how many other users found the review helpful or agreed with the sentiments expressed. It serves as a measure of the review's relevancy and impact.
• at: The timestamp of when the review was posted. This column includes the date and time when the review was submitted. It is crucial for tracking the temporal distribution of reviews and analyzing trends over time.

Collection Methods

• Data Source: The data is collected from user reviews submitted through the ChatGPT Android App's review section on the Google Play Store.
• Frequency: The dataset is updated daily to capture the most recent user feedback and ratings.
• Automation: An automated script is used to scrape and compile the reviews, ensuring that the dataset is current and comprehensive.
• Data Cleaning: Basic preprocessing is performed to ensure data quality, such as removing duplicates and handling missing values.

In January 2024, ChatGPT online domain chat.openai.com registered over **** percent of its traffic as originating in the United States. Users based in India generated approximately **** percent of the total visits to the chatbot platform, while users in Indonesia accounted for *** percent of the total visits to the website. Visits from Brazil represented the fourth-largest group for the platform, generating more than **** percent of the total traffic recorded in the examined period.

The AI chatbot race between Claude and ChatGPT is reshaping how people work and communicate. Whether drafting business code or fast-tracking creative tasks, these tools power productivity and insight across industries. For instance, enterprise teams integrate Claude’s advanced reasoning into analytics platforms, while marketers tap ChatGPT for on-demand content ideation....

Weekly active user statistics for ChatGPT from January 2023 to April 2025.

The rivalry between ChatGPT and Google Gemini defines the generative AI landscape. ChatGPT remains the leader in active engagement, while Gemini closes the gap through mass distribution. From corporate reports to web traffic studies, figures speak clearly about adoption, reach, and momentum. Explore what makes each platform stand out, and what...

As of June 2025, the largest group of ChatGPT users in Poland were women, over *** million.

Don't forget to hit the UpVote🙏🙏

The DataSet consists of user reviews of ChatGPT, including Textual Feedback, Ratings, and Review Dates. The Reviews Range from brief comments to more detailed feedback by covering a wide range of user sentiments. The ratings are on a scale of 1 to 5, representing varying levels of Satisfaction. The dataset spans multiple months, providing a temporal dimension for analysis. Each review is accompanied by a timestamp, allowing for Time-Series analysis of sentiment trends.

1. Review Id:

• Description: A unique identifier for each review.
• Data Type: String (UUID format).

2. Review:

• Description: The text of the user review. This provides qualitative feedback about the app.
• Data Type: String

3. Ratings:

• Description: User-provided ratings on a scale (likely 1-5) to indicate their level of satisfaction.
• Data Type: Integer
• Range: 1 (lowest) to 5 (highest)

4. Review Date:

• Description: The timestamp when the review was submitted.
• Data Type: Date_Time
• Format: MM/DD/YYYY HH:MM

As of June 2025, the largest group of ChatGPT users in Poland was people aged ********.

Analysis of 13,252 publicly shared ChatGPT conversations by WebFX to uncover usage statistics - prompt length, message count, question vs command distribution, use-case categories.

We have compiled a dataset that consists of textual articles including common terminology, concepts and definitions in the field of computer science, artificial intelligence, and cyber security. This dataset consists of both human-generated text and OpenAI’s ChatGPT-generated text. Human-generated answers were collected from different computer science dictionaries and encyclopedias including “The Encyclopedia of Computer Science and Technology” and "Encyclopedia of Human-Computer Interaction". AI-generated content in our dataset was produced by simply posting questions to OpenAI’s ChatGPT and manually documenting the resulting responses. A rigorous data-cleaning process has been performed to remove unwanted Unicode characters, styling and formatting tags. To structure our dataset for binary classification, we combined both AI-generated and Human-generated answers into a single column and assigned appropriate labels to each data point (Human-generated = 0 and AI-generated = 1).

This creates our article-level dataset (article_level_data.csv) which consists of a total of 1018 articles, 509 AI-generated and 509 Human-generated. Additionally, we have divided each article into its sentences and labelled them accordingly. This is mainly to evaluate the performance of classification models and pipelines when it comes to shorter sentence-level data points. This constructs our sentence-level dataset (sentence_level_data.csv) which consists of a total of 7344 entries (4008 AI-generated and 3336 Human-generated).

We appreciate it, if you cite the following article if you happen to use this dataset in any scientific publication:

Maktab Dar Oghaz, M., Dhame, K., Singaram, G., & Babu Saheer, L. (2023). Detection and Classification of ChatGPT Generated Contents Using Deep Transformer Models. Frontiers in Artificial Intelligence.

https://www.techrxiv.org/users/692552/articles/682641/master/file/data/ChatGPT_generated_Content_Detection/ChatGPT_generated_Content_Detection.pdf

This dataset presents ChatGPT usage patterns across different age groups, showing the percentage of users who have followed its advice, used it without following advice, or have never used it, based on a 2025 U.S. survey.

Most Used Features and Usage Statistics By September 2025, ChatGPT boasts ~800 million weekly users and 355 million monthly active users, with 2.6 billion daily messages across 700 million users. It's the #1 AI tool globally (60.6% market share), especially among under-25s (45% of users). Daily usage: 9% of 18-24-year-olds. Top use cases (from OpenAI's 2025 user study):

Everyday Productivity (52% of sessions): Email drafting, brainstorming, task lists. Content Creation/Writing (28%): Essays, social media, code snippets. Research & Learning (15%): Summaries, explanations, tutoring. Coding/Development (12%): Debugging, automation scripts. Creative Tools (e.g., Image Gen in GPT-4o/5, 10%): Art, voice chats.

Enterprise adoption hit 80% of Fortune 500 companies by mid-2025, with mobile apps driving 40% of traffic. Efficiency Metrics Efficiency in ChatGPT refers to speed, cost, productivity gains, and resource use. GPT-5 processes queries 3x faster than GPT-4o (under 1s for simple tasks) while using 50% less compute. Key metrics:

A comparative table of response and citation characteristics for ChatGPT and Google AI Overview in 2025, including response length, sentence length, number of sources, duplication rate, domain overlap, subjectivity, readability, AI marker usage, domain age share, and semantic similarity.

As of June 2025, the largest group of ChatGPT users in Poland was people living in villages, nearly *** million.

The dataset is focused on exploring the relationship between the performance of Chegg's stock prices and the growth of ChatGPT users over time. Chegg is an education technology company that provides online learning resources. The company has experienced significant growth in recent years, driven in part by COVID-19.

However, Chegg's stock price dropped due to the shift of some of its users from Chegg's platform to ChatGPT. This shift in user behavior can be attributed to ChatGPT's advanced AI capabilities, which allow it to provide personalized and accurate assistance to users.

The dataset includes five tables that provide valuable insights into the relationship between Chegg stock prices and ChatGPT user growth, with a particular focus on the impact of the user shift on Chegg's stock performance. The first three tables contain weekly, monthly, and daily data on Chegg's stock performance, including information on the opening and closing prices, highest and lowest prices, and trading volume. These tables also include information on significant events that may have impacted the company's stock prices, such as product launches, partnerships, and earnings reports.

The fourth table provides data on the number of ChatGPT users recorded over the past months. This table includes information on the total number of users, as well as data on user growth rates and trends. The data in this table can be used to identify correlations between ChatGPT user growth and changes in Chegg's stock performance.

The fifth and final table provides the latest updates on ChatGPT, including information on new features, updates, and user feedback. This table is designed to keep the dataset current and relevant, providing users with the latest information on ChatGPT and its impact on Chegg's stock performance.

Overall, this dataset provides a valuable resource for anyone interested in understanding the impact of user behavior on the stock performance of companies like Chegg that operate in the education technology sector. It offers a comprehensive view of the data and trends over time, which can be used to identify patterns and correlations that can inform investment decisions and strategic planning.

This dataset shows the types of advice users sought from ChatGPT based on a 2025 U.S. survey, including education, financial, medical, and legal topics.

ChatGPT is used most widely among those between ** and ** around the world. The youngest group, those under **, are the second largest userbase, and together those under ** account for over ** percent of ChatGPT users. It is perhaps unsurprising that the younger age brackets use the chatbot more than older as that is the common trend with new technologies. Male users were far more numerous than female users, with males representing over ** percent of total users in 2023.