ChatGPT is used most widely among those between 25 and 34 around the world. The youngest group, those under 24, are the second largest userbase, and together those under 34 account for over 60 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 65 percent of total users in 2023.
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ChatGPT has taken the world by storm, setting a record for the fastest app to reach a 100 million users, which it hit in two months. The implications of this tool are far-reaching, universities...
In a survey conducted across **** Southeast Asian countries in February 2023, almost half of the respondents selected collection of personal data as one of the concerns they had regarding the usage of chatbots like ChatGPT. In contrast, ethical issues related to data privacy and intellectual property were a concern for ** percent of the respondents.
In January 2023, ChatGPT registered over nine million interactions from users in Italy, up by over 300 percent compare to the previous month. By comparison, the OpenAI website registered 1.2 million actions performed by Italian users. At the end of March 2023, the main national privacy regulator in Italy prompted OpenAI to provide information on how and why the company collects user data, if the company wanted to avoid seeing its access to the Italian market blocked.
A 2023 survey found that approximately ** percent of respondents in Indonesia reported using ChatGPT on a weekly basis for various purposes, from work to entertainment. Meanwhile, around ** percent of respondents stated that they rarely used ChatGPT.
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A major challenge of our time is reducing disparities in access to and effective use of digital technologies, with recent discussions highlighting the role of AI in exacerbating the digital divide. We examine user characteristics that predict usage of the AI-powered conversational agent ChatGPT. We combine behavioral and survey data in a web tracked sample of N=1376 German citizens to investigate differences in ChatGPT activity (usage, visits, and adoption) during the first 11 months from the launch of the service (November 30, 2022). Guided by a model of technology acceptance (UTAUT-2), we examine the role of socio-demographics commonly associated with the digital divide in ChatGPT activity and explore further socio-political attributes identified via stability selection in Lasso regressions. We confirm that lower age and higher education affect ChatGPT usage, but neither gender nor income do. We find full-time employment and more children to be barriers to ChatGPT activity. Using a variety of social media was positively associated with ChatGPT activity. In terms of political variables, political knowledge and political self-efficacy as well as some political behaviors such as voting, debating political issues online and offline and political action online were all associated with ChatGPT activity, with online political debating and political self-efficacy negatively so. Finally, need for cognition and communication skills such as writing, attending meetings, or giving presentations, were also associated with ChatGPT engagement, though chairing/organizing meetings was negatively associated. Our research informs efforts to address digital disparities and promote digital literacy among underserved populations by presenting implications, recommendations, and discussions on ethical and social issues of our findings.
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.
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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.
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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.
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Comprehensive ChatGPT statistics covering 800 million weekly users, $300 billion valuation, market share, demographics, and technical specifications for 2025.
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This dataset presents ChatGPT usage patterns across U.S. Census regions, based on a 2025 nationwide survey. It tracks how often users followed, partially used, or never used ChatGPT by state region.
In March 2025, ChatGPT’s mobile app recorded over 64.26 million App Store and Google Play downloads worldwide. Google's Gemini AI Assistant mobile app was released on February 8, 2024, and was initially available in the U.S. market only. In the same month, the app registered around 13.92 million downloads. Regional preferences shape AI app adoption ChatGPT has a strong global presence with over 400.61 million monthly active users in February 2025, but regional preferences vary. In the United States, ChatGPT had a 45 percent download market share, compared to Google Gemini's 11 percent. However, Gemini emerged as the preferred generative AI app in India, representing a 52 percent market share. This competitive landscape now also includes Chinese-based players like ByteDance's Doubao and DeepSeek, indicating an even more diverse and evolving AI worldwide ecosystem. The AI-powered revolution in online search The global AI market has experienced substantial growth, exceeding 184 billion U.S. dollars in 2024 and projected to surpass 826 billion U.S. dollars by 2030. This expansion is mirrored in user behavior, with around 15 million adults in the United States using AI-powered tools as their first option for online search in 2024. Additionally, 68 percent of U.S. adults reported the use of AI-powered search engines for exploring new topics in 2024, with another 44 percent of respondents utilizing these tools to learn or explain concepts.
Supplemental Material Contents: · 1-Demographic Information.xlsx: contains the demographic information of the participants in the study. · 2-Forms.zip: contains the forms and questionnaires used to collect data for the experiment: demographic form, pre-study, post-study, and AAR/AI questionnaires. · 3-GitHub-Repository.zip: a copy of the GitHub repository used in the study. · 4-Tutorial Scripts.zip: script used in the experiment with the groups to be consistent with all participants. · 5-Logs-Rubric-Grades.zip: contains the participant data log (commit and PR), rubric for grading submissions, and grades. · 6-RQ1-Data-and-Analysis.zip: contains the data and analysis with respect to RQ1. · 7-RQ2-Data-and-Analysis.zip: contains the data and analysis with respect to RQ2. · 8-Participant Prompts.xlsx: contains the experimental group participant prompts with ChatGPT. 2. Forms.zip The forms zip contains the following files: · Demographics.pdf: a form used to collect demographic information from participants before the study. · Control Pre-Study Questionnaire.pdf: Pre study questionnaire control group (Self-Efficacy Questionnaire) · Control Post-Study Questionnaire.pdf: Post study questionnaire control group (NASA-TLX, Self-Efficacy Questionnaire) · Treatment - AAR_AI task.pdf: Pre and Post task AAR/AI questionnaire for experimental group. · Experimental Pre-Study Questionnaire.pdf: Pre study questionnaire experimental group (Self-Efficacy Questionnaire, Question for Familiarity with AI) · Experimental-Post Study Questionnaire.pdf: Post study questionnaire experimental group (AAR/AI step 7, Continuance Intention, NASA-TLX, HAI Guideline Questions, Self-Efficacy Questionnaire) 3-GitHub-Repository.zip The GitHub repository used in the study: contains the main.py code file and the Readme.md file (having the written instructions for the participants). 4-Tutorial Scripts.zip Contains: · Control-Script.pdf: Script for the control group. · Experimental-Script.pdf: Script for the experimental group. 5-Logs-Rubric-Grades.zip · rubric.pdf: Created rubric for grading task performance. · GitHub-Task3-Log.xlsx: File containing the data regarding the status of commit made and PR raised for each participant. · grades.xlsx: Detailed grades for each participant in experimental (treatment) and control groups. 6-RQ1-Data-and-Analysis.zip Note: The term 'treatment' has been used in the files of this folder to represent the experimental group: participants using ChatGPT for the tasks. · NASA TLX: folder containing the participant data (TLX.xlsx), code for statistical analysis (Stat-TLX.py) and statistical reports (analysis-TLX.csv). · Task Performance: folder containing the participant data (grades.xlsx & Scores.xlsx(overall grade)), code for statistical analysis (Stat-Correctness.py) and statistical reports (analysis.csv). · Self-Efficacy: folder containing: o Self-Efficacy-detailed.xlsx: participant data o Paired Stats: folder containing data (Total Self Efficacy.csv), code for statistical analysis(paired-stats.py), and statistical reports (analysis.csv). o Box plot: folder containing the code for generating the box plot and its output. · Continuance Intention.xlsx: participant data (experimental) for continuance intention of ChatGPT. · Stat-Table-H1-2-Paper.xlsx: Statistics table for NASA TLX and task performance as presented in the paper. 7-RQ2-Data-and-Analysis.zip · AAR_AI-Responses.xlsx: AAR/AI responses filled by participants in experimental group. · Quotation Manager-Faults&Conseq.xlsx: Contains the quotations from AAR/AI responses along with corresponding codes. Also contains the quotes that link faults to consequences in a separate sheet. · Codebook.xlsx: The final codebook (faults and consequences). · HAI-data.xlsx: Contains the reported guideline violations along with disaggregated analysis (grouped by gender). · Likert Plot-HAI: folder contains the code for generating the Likert plot figure presented in the paper.
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OpenAI Statistics: OpenAI, Inc. is an AI company based in San Francisco, California, and was started in December 2015. Its main goal is to build powerful and safe AI systems. OpenAI wants to create smart machines, called AGI, that can do most jobs better than humans, especially the ones that add economic value. This is also best known for developing advanced AI tools like ChatGPT, designed to solve real-world problems and improve daily life. Its mission is to make powerful AI available to everyone in a way that benefits society.
This article includes several current statistical analyses that are taken from different insights, which will guide in understanding the topic effectively as it covers the overall market, sales, user demographics, usage shares, website traffic, and many other factors.
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Survey data on ChatGPT Earns the Confidence of Users
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This dataset presents how much users trust ChatGPT across different advice categories, including career, education, financial, legal, and medical advice, based on a 2025 U.S. survey.
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*both authors contributed equally
Automated query script for automated language bias studies in GPT 3-5
Dataset of the paper "How User Language Affects Conflict Fatality Estimates in ChatGPT" preprint available on ArXiv
This dataset provides a collection of user reviews for the ChatGPT mobile application on iOS. It captures valuable user insights and sentiments, making it suitable for understanding customer satisfaction, evaluating app performance, and identifying emerging trends. The data was gathered by scraping ChatGPT reviews from the App Store.
The dataset is typically provided in a CSV file format. It includes 2058 unique date values and 2257 unique review texts. The reviews span from 18th May 2023 to 25th July 2023. Review counts by period are as follows: * 18th May 2023 - 25th May 2023: 1,475 reviews * 25th May 2023 - 1st June 2023: 267 reviews * 1st June 2023 - 7th June 2023: 117 reviews * 7th June 2023 - 14th June 2023: 82 reviews * 14th June 2023 - 21st June 2023: 60 reviews * 21st June 2023 - 28th June 2023: 59 reviews * 28th June 2023 - 4th July 2023: 73 reviews * 4th July 2023 - 11th July 2023: 45 reviews * 11th July 2023 - 18th July 2023: 57 reviews * 18th July 2023 - 25th July 2023: 57 reviews
Rating distribution is also available: * 1.00 - 1.40 stars: 495 reviews * 1.80 - 2.20 stars: 139 reviews * 3.00 - 3.40 stars: 220 reviews * 3.80 - 4.20 stars: 304 reviews * 4.60 - 5.00 stars: 1,134 reviews
This dataset is ideal for: * Sentiment analysis to gauge user emotions and opinions regarding the ChatGPT app. * Performance evaluation to identify factors contributing to high or low user ratings. * Pattern identification to uncover recurring themes and common issues in user feedback.
The dataset covers reviews globally, spanning a time range from 18th May 2023 to 25th July 2023.
CC-BY-NC
Original Data Source: ChatGPT App Reviews
This dataset provides a daily-updated collection of user reviews and ratings specifically for the ChatGPT Android application. It includes crucial information such as the review text, associated ratings, and the dates when reviews were posted. The dataset also details the relevancy of each review. It serves as a valuable resource for understanding user sentiment, tracking app performance over time, and analysing trends within the AI and Large Language Model (LLM) application landscape.
The dataset is primarily available in a tabular format, typically a CSV file, facilitating easy integration and analysis. It comprises over 637,000 unique reviews, reflecting a substantial volume of user feedback. This dataset is updated on a daily basis, ensuring access to the latest user opinions and rating trends. While the exact file size is not specified, the number of records indicates a considerable volume of data.
This dataset is ideal for various analytical applications, including: * Sentiment Analysis: Extracting and understanding user emotions and opinions towards the ChatGPT Android app. * Natural Language Processing (NLP) Tasks: Training and testing NLP models for text classification, entity recognition, and language generation based on real-world user input. * App Performance Monitoring: Tracking changes in user ratings and feedback over time to gauge application performance and identify areas for improvement. * Market Research: Gaining insights into user perception of AI and LLM applications within the mobile market. * Competitive Analysis: Comparing user feedback for the ChatGPT app against other similar applications. * Feature Prioritisation: Identifying desired features or common pain points mentioned by users to inform product development.
This dataset offers global coverage, collecting reviews from users across the world. The time range for the reviews spans from 25 July 2023 to 30 June 2025. This extensive period allows for longitudinal studies of user sentiment and app evolution. It captures feedback from a diverse demographic of ChatGPT Android app users. Some data points, such as appVersion
, may occasionally have null values.
CC-BY-NC-SA
Original Data Source: ChatGPT reviews [DAILY UPDATED]
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This dataset contains information related to ChatGPT, OpenAI's conversational AI model, gathered from social media. It includes keywords such as "chatgpt" and "chat gpt", as well as associated hashtags and mentions. The dataset's purpose is to help in understanding public opinion, identifying trends, and exploring potential applications of ChatGPT. By analysing tweet volume, sentiment, user engagement, and the influence of key AI events, this dataset offers valuable insights for various stakeholders.
This dataset is provided as a CSV file and includes data on 500,000 tweets. The dataset consists of two CSV files: an originally scraped dataset and a preprocessed dataset.
This dataset is ideal for: * Understanding public sentiment and trends surrounding ChatGPT. * Analysing tweet volume and user engagement related to AI-powered conversational technologies. * Exploring the influence of key AI events on social media discussions. * Supporting research into the societal impact and adoption of conversational AI.
The dataset covers the period from January to March 2023. The data collected is global in scope, capturing public opinion on social media platforms.
CC0
Original Data Source: 500k ChatGPT-related Tweets Jan-Mar 2023
ChatGPT is used most widely among those between 25 and 34 around the world. The youngest group, those under 24, are the second largest userbase, and together those under 34 account for over 60 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 65 percent of total users in 2023.