25 datasets found
  1. e

    ChatGPT Usage by U.S. Census Region – Survey Data

    • expresslegalfunding.com
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    Updated Sep 10, 2025
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    Express Legal Funding (2025). ChatGPT Usage by U.S. Census Region – Survey Data [Dataset]. https://expresslegalfunding.com/chatgpt-study/
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Sep 10, 2025
    Dataset authored and provided by
    Express Legal Funding
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Pacific, Mountain, New England, South Atlantic, Middle Atlantic, East North Central, East South Central, West North Central, West South Central
    Description

    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.

  2. Datasets .csv

    • figshare.com
    txt
    Updated Jan 24, 2024
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    Yaser Alhasawi (2024). Datasets .csv [Dataset]. http://doi.org/10.6084/m9.figshare.25053146.v1
    Explore at:
    txtAvailable download formats
    Dataset updated
    Jan 24, 2024
    Dataset provided by
    figshare
    Authors
    Yaser Alhasawi
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The dataset for this research project was meticulously constructed to investigate the adoption of ChatGPT among students in the United States. The primary objective was to gain insights into the technological barriers and resistances faced by students in integrating ChatGPT into their information systems. The dataset was designed to capture the diverse adoption patterns among students in various public and private schools and universities across the United States. By examining adoption rates, frequency of usage, and the contexts in which ChatGPT is employed, the research sought to provide a comprehensive understanding of how students are incorporating this technology into their information systems. Moreover, by including participants from diverse educational institutions, the research sought to ensure a comprehensive representation of the student population in the United States. This approach aimed to provide nuanced insights into how factors such as educational background, institution type, and technological familiarity influence ChatGPT adoption.

  3. e

    ChatGPT Usage by Age Group – Survey Data

    • expresslegalfunding.com
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    Updated Sep 10, 2025
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    Express Legal Funding (2025). ChatGPT Usage by Age Group – Survey Data [Dataset]. https://expresslegalfunding.com/chatgpt-study/
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Sep 10, 2025
    Dataset authored and provided by
    Express Legal Funding
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    60+, 18–29, 30–44, 45–60
    Description

    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.

  4. e

    ChatGPT Usage by Gender – Survey Data

    • expresslegalfunding.com
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    Updated Sep 10, 2025
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    Express Legal Funding (2025). ChatGPT Usage by Gender – Survey Data [Dataset]. https://expresslegalfunding.com/chatgpt-study/
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Sep 10, 2025
    Dataset authored and provided by
    Express Legal Funding
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Men, Women
    Description

    This dataset shows how men and women in the U.S. reported using ChatGPT in a 2025 survey, including whether they followed its advice or chose not to use it.

  5. e

    Types of ChatGPT Advice Used – Survey Data

    • expresslegalfunding.com
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    Updated Sep 10, 2025
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    Express Legal Funding (2025). Types of ChatGPT Advice Used – Survey Data [Dataset]. https://expresslegalfunding.com/chatgpt-study/
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Sep 10, 2025
    Dataset authored and provided by
    Express Legal Funding
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Legal Advice, Career Advice, Educational Help, Financial Advice, Medical Information, Relationship Advice, Mental Health Topics, News / Current Events, Product Recommendations
    Description

    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.

  6. h

    scraped-chatgpt-conversations

    • huggingface.co
    Updated Apr 6, 2023
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    Arya Nistane (2023). scraped-chatgpt-conversations [Dataset]. https://huggingface.co/datasets/ar852/scraped-chatgpt-conversations
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 6, 2023
    Authors
    Arya Nistane
    Description

    Dataset Card for Dataset Name

      Dataset Summary
    

    scraped-chatgpt-conversations contains ~100k conversations between a user and chatgpt that were shared online through reddit, twitter, or sharegpt. For sharegpt, the conversations were directly scraped from the website. For reddit and twitter, images were downloaded from submissions, segmented, and run through an OCR pipeline to obtain a conversation list. For information on how the each json file is structured, please see… See the full description on the dataset page: https://huggingface.co/datasets/ar852/scraped-chatgpt-conversations.

  7. e

    Outcome of ChatGPT Advice – Survey Data

    • expresslegalfunding.com
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    Updated Sep 10, 2025
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    Express Legal Funding (2025). Outcome of ChatGPT Advice – Survey Data [Dataset]. https://expresslegalfunding.com/chatgpt-study/
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Sep 10, 2025
    Dataset authored and provided by
    Express Legal Funding
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Unsure – Not sure yet, Helpful – It led to a good result, Neutral – It made no real difference, Harmful – It caused problems or a bad result
    Description

    This dataset summarizes how ChatGPT users rated the outcomes of the advice they received, including whether it was helpful, harmful, neutral, or uncertain, based on a 2025 U.S. survey.

  8. h

    wildchat-filtered

    • huggingface.co
    Updated Oct 1, 2025
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    Rayon Labs (2025). wildchat-filtered [Dataset]. https://huggingface.co/datasets/rayonlabs/wildchat-filtered
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    Dataset updated
    Oct 1, 2025
    Authors
    Rayon Labs
    License

    https://choosealicense.com/licenses/odc-by/https://choosealicense.com/licenses/odc-by/

    Description

    WildChat Filtered Dataset

    This is a filtered version of the WildChat-4.8M dataset.

      Dataset Description
    

    This dataset contains 3,199,860 conversations between human users and ChatGPT, filtered to keep only the essential conversation structure.

      Data Structure
    

    Each conversation contains only:

    conversations: A list of message objects with: role: Either "user" or "assistant" content: The text content of the message

    All other metadata (timestamps, moderation… See the full description on the dataset page: https://huggingface.co/datasets/rayonlabs/wildchat-filtered.

  9. e

    ChatGPT Trust Levels by Advice Category – Survey Data

    • expresslegalfunding.com
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    Updated Sep 10, 2025
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    Express Legal Funding (2025). ChatGPT Trust Levels by Advice Category – Survey Data [Dataset]. https://expresslegalfunding.com/chatgpt-study/
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Sep 10, 2025
    Dataset authored and provided by
    Express Legal Funding
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Legal Advice, Career Advice, Educational Help, Financial Advice, Medical Information, Relationship Advice, Mental Health Topics, News / Current Events, Product Recommendations
    Description

    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.

  10. e

    ChatGPT vs. Google Trust Comparison – Survey Data

    • expresslegalfunding.com
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    Updated Sep 10, 2025
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    Express Legal Funding (2025). ChatGPT vs. Google Trust Comparison – Survey Data [Dataset]. https://expresslegalfunding.com/chatgpt-study/
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Sep 10, 2025
    Dataset authored and provided by
    Express Legal Funding
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Much less, Much more, Slightly less, Slightly more, About the same
    Description

    This dataset compares how much U.S. adults trust ChatGPT relative to Google Search, including responses from a 2025 national survey measuring perceptions of AI accuracy and reliability.

  11. h

    awesome-chatgpt-prompts

    • huggingface.co
    Updated Dec 15, 2023
    + more versions
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    Fatih Kadir Akın (2023). awesome-chatgpt-prompts [Dataset]. https://huggingface.co/datasets/fka/awesome-chatgpt-prompts
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 15, 2023
    Authors
    Fatih Kadir Akın
    License

    https://choosealicense.com/licenses/cc0-1.0/https://choosealicense.com/licenses/cc0-1.0/

    Description

    🧠 Awesome ChatGPT Prompts [CSV dataset]

    This is a Dataset Repository of Awesome ChatGPT Prompts View All Prompts on GitHub

      License
    

    CC-0

  12. Chatbot Market Analysis, Size, and Forecast 2025-2029: North America (US and...

    • technavio.com
    pdf
    Updated Feb 1, 2025
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    Technavio (2025). Chatbot Market Analysis, Size, and Forecast 2025-2029: North America (US and Canada), Europe (France, Germany, Italy, and UK), Middle East and Africa (Egypt, KSA, Oman, and UAE), APAC (China, India, and Japan), South America (Argentina and Brazil), and Rest of World (ROW) [Dataset]. https://www.technavio.com/report/chatbot-market-industry-analysis
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Feb 1, 2025
    Dataset provided by
    TechNavio
    Authors
    Technavio
    License

    https://www.technavio.com/content/privacy-noticehttps://www.technavio.com/content/privacy-notice

    Time period covered
    2025 - 2029
    Description

    Snapshot img

    Chatbot Market Size 2025-2029

    The chatbot market size is forecast to increase by USD 9.63 billion, at a CAGR of 42.9% between 2024 and 2029. Several benefits associated with using chatbots solutions will drive the chatbot market.

    Major Market Trends & Insights

    APAC dominated the market and accounted for a 37% growth during the forecast period.
    By End-user - Retail segment was valued at USD 210.60 billion in 2023
    By Product - Solutions segment accounted for the largest market revenue share in 2023
    

    Market Size & Forecast

    Market Opportunities: USD 1.00 billion
    Market Future Opportunities: USD 9.63 billion 
    CAGR : 42.9%
    APAC: Largest market in 2023
    

    Market Summary

    The market is a dynamic and evolving landscape, characterized by the integration of advanced technologies and innovative applications. Core technologies such as natural language processing (NLP) and machine learning (ML) enable chatbots to understand and respond to user queries in a conversational manner, transforming customer engagement across industries. However, the lack of standardization and awareness surrounding chatbot services poses a challenge to market growth. As of now, chatbots are increasingly being adopted in various sectors, including healthcare, finance, and e-commerce, with customer service being the primary application. According to recent estimates, over 50% of businesses are expected to invest in chatbots by 2025.
    In terms of service types, chatbots can be categorized into rule-based and AI-powered, each offering unique benefits and challenges. Key companies, such as Microsoft, IBM, and Google, are continuously pushing the boundaries of chatbot technology, introducing new features and capabilities. Regulatory frameworks, including GDPR and HIPAA, play a crucial role in shaping the market landscape. Looking ahead, the forecast period presents significant opportunities for growth, as chatbots continue to reshape the way businesses interact with their customers. Related markets such as voice assistants and conversational AI also contribute to the broader context of the market.
    Stay tuned for more insights and analysis on this continuously unfolding market.
    

    What will be the Size of the Chatbot Market during the forecast period?

    Get Key Insights on Market Forecast (PDF) Request Free Sample

    How is the Chatbot Market Segmented and what are the key trends of market segmentation?

    The chatbot industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

    End-user
    
      Retail
      BFSI
      Government
      Travel and hospitality
      Others
    
    
    Product
    
      Solutions
      Services
    
    
    Deployment
    
      Cloud-Based
      On-Premise
      Hybrid
    
    
    Application
    
      Customer Service
      Sales and Marketing
      Healthcare Support
      E-Commerce Assistance
    
    
    Geography
    
      North America
    
        US
        Canada
    
    
      Europe
    
        France
        Germany
        Italy
        UK
    
    
      Middle East and Africa
    
        Egypt
        KSA
        Oman
        UAE
    
    
      APAC
    
        China
        India
        Japan
    
    
      South America
    
        Argentina
        Brazil
    
    
      Rest of World (ROW)
    

    By End-user Insights

    The retail segment is estimated to witness significant growth during the forecast period.

    The market is experiencing significant growth, with adoption in various sectors escalating at a remarkable pace. According to recent reports, the chatbot industry is projected to expand by 25% in the upcoming year, while current market penetration hovers around 27%. This growth can be attributed to the increasing adoption of conversational AI platforms in customer service and e-commerce applications. Unsupervised learning techniques and machine learning models play a pivotal role in chatbot development, enabling natural language processing and understanding. Dialog management systems, including F1-score calculation and dialogue state tracking, ensure effective conversation flow. Human-in-the-loop training and contextual understanding further enhance chatbot performance.

    Natural language generation, intent recognition technology, and knowledge graph integration are essential components of advanced chatbot systems. Multi-lingual chatbot support and speech-to-text conversion cater to a diverse user base. Reinforcement learning methods and deep learning algorithms enable chatbots to learn and improve from user interactions. Chatbot development platforms employ various data augmentation methods and active learning strategies to create training datasets for transfer learning applications. Question answering systems and voice-enabled chatbot features provide seamless user experiences. Sentiment analysis techniques and user interface design contribute to enhancing customer engagement and satisfaction. Conversational flow design and response generation models ensure e

  13. e

    Trust in ChatGPT vs. Human Experts – Survey Data

    • expresslegalfunding.com
    html
    Updated Sep 10, 2025
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    Express Legal Funding (2025). Trust in ChatGPT vs. Human Experts – Survey Data [Dataset]. https://expresslegalfunding.com/chatgpt-study/
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Sep 10, 2025
    Dataset authored and provided by
    Express Legal Funding
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Yes – Trust ChatGPT more than a human expert, No – Do not trust ChatGPT more than a human expert
    Description

    This dataset shows the percentage of U.S. adults who say they trust ChatGPT more than a human expert, based on a 2025 national AI trust survey.

  14. d

    AI in Consumer Decision Making | Global Coverage | 190+ Countries

    • datarade.ai
    .json, .csv, .xls
    Updated Aug 21, 2025
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    Rwazi (2025). AI in Consumer Decision Making | Global Coverage | 190+ Countries [Dataset]. https://datarade.ai/data-products/ai-in-consumer-decision-making-global-coverage-190-count-rwazi
    Explore at:
    .json, .csv, .xlsAvailable download formats
    Dataset updated
    Aug 21, 2025
    Dataset authored and provided by
    Rwazihttp://rwazi.com/
    Area covered
    Saint Lucia, Bolivia (Plurinational State of), Trinidad and Tobago, Guam, Gibraltar, Israel, Liechtenstein, Turkmenistan, United States of America, Cook Islands
    Description

    AI in Consumer Decision-Making: Global Zero-Party Dataset

    This dataset captures how consumers around the world are using AI tools like ChatGPT, Perplexity, Gemini, Claude, and Copilot to guide their purchase decisions. It spans multiple product categories, demographics, and geographies, mapping the emerging role of AI as a decision-making companion across the consumer journey.

    What Makes This Dataset Unique

    Unlike datasets inferred from digital traces or modeled from third-party assumptions, this collection is built entirely on zero-party data: direct responses from consumers who voluntarily share their habits and preferences. That means the insights come straight from the people making the purchases, ensuring unmatched accuracy and relevance.

    For FMCG leaders, retailers, and financial services strategists, this dataset provides the missing piece: visibility into how often consumers are letting AI shape their decisions, and where that influence is strongest.

    Dataset Structure

    Each record is enriched with: Product Category – from high-consideration items like electronics to daily staples such as groceries and snacks. AI Tool Used – identifying whether consumers turn to ChatGPT, Gemini, Perplexity, Claude, or Copilot. Influence Level – the percentage of consumers in a given context who rely on AI to guide their choices. Demographics – generational breakdowns from Gen Z through Boomers. Geographic Detail – city- and country-level coverage across Africa, LATAM, Asia, Europe, and North America.

    This structure allows filtering and comparison across categories, age groups, and markets, giving users a multidimensional view of AI’s impact on purchasing.

    Why It Matters

    AI has become a trusted voice in consumers’ daily lives. From meal planning to product comparisons, many people now consult AI before making a purchase—often without realizing how much it shapes the options they consider. For brands, this means that the path to purchase increasingly runs through an AI filter.

    This dataset provides a comprehensive view of that hidden step in the consumer journey, enabling decision-makers to quantify: How much AI shapes consumer thinking before they even reach the shelf or checkout. Which product categories are most influenced by AI consultation. How adoption varies by geography and generation. Which AI platforms are most commonly trusted by consumers.

    Opportunities for Business Leaders

    FMCG & Retail Brands: Understand where AI-driven decision-making is already reshaping category competition. Marketers: Identify demographic segments most likely to consult AI, enabling targeted strategies. Retailers: Align assortments and promotions with the purchase patterns influenced by AI queries. Investors & Innovators: Gauge market readiness for AI-integrated commerce solutions.

    The dataset doesn’t just describe what’s happening—it opens doors to the “so what” questions that define strategy. Which categories are becoming algorithm-driven? Which markets are shifting fastest? Where is the opportunity to get ahead of competitors in an AI-shaped funnel?

    Why Now

    Consumer AI adoption is no longer a forecast; it is a daily behavior. Just as search engines once rewrote the rules of marketing, conversational AI is quietly rewriting how consumers decide what to buy. This dataset offers an early, detailed view into that change, giving brands the ability to act while competitors are still guessing.

    What You Get

    Users gain: A global, city-level view of AI adoption in consumer decision-making. Cross-category comparability to see where AI influence is strongest and weakest. Generational breakdowns that show how adoption differs between younger and older cohorts. AI platform analysis, highlighting how tool preferences vary by region and category. Every row is powered by zero-party input, ensuring the insights reflect actual consumer behavior—not modeled assumptions.

    How It’s Used

    Leverage this data to:

    Validate strategies before entering new markets or categories. Benchmark competitors on AI readiness and influence. Identify growth opportunities in categories where AI-driven recommendations are rapidly shaping decisions. Anticipate risks where brand visibility could be disrupted by algorithmic mediation.

    Core Insights

    The full dataset reveals: Surprising adoption curves across categories where AI wasn’t expected to play a role. Geographic pockets where AI has already become a standard step in purchase decisions. Demographic contrasts showing who trusts AI most—and where skepticism still holds. Clear differences between AI platforms and the consumer profiles most drawn to each.

    These patterns are not visible in traditional retail data, sales reports, or survey summaries. They are only captured here, directly from the consumers themselves.

    Summary

    Winning in FMCG and retail today means more than getting on shelves, capturing price points, or running promotions. It means understanding the invisible algorithms consumers are ...

  15. h

    chats-data-2023-10-16

    • huggingface.co
    Updated Oct 16, 2023
    + more versions
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    Collective Cognition (2023). chats-data-2023-10-16 [Dataset]. https://huggingface.co/datasets/CollectiveCognition/chats-data-2023-10-16
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 16, 2023
    Dataset authored and provided by
    Collective Cognition
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Dataset Card for "Collective Cognition ChatGPT Conversations"

      Dataset Description
    
    
    
    
    
      Dataset Summary
    

    The "Collective Cognition ChatGPT Conversations" dataset is a collection of chat logs between users and the ChatGPT model. These conversations have been shared by users on the "Collective Cognition" website. The dataset provides insights into user interactions with language models and can be utilized for multiple purposes, including training, research, and… See the full description on the dataset page: https://huggingface.co/datasets/CollectiveCognition/chats-data-2023-10-16.

  16. h

    wildbio

    • huggingface.co
    Updated Dec 16, 2024
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    David Steinberg (2024). wildbio [Dataset]. https://huggingface.co/datasets/david4096/wildbio
    Explore at:
    Dataset updated
    Dec 16, 2024
    Authors
    David Steinberg
    Description

    The intersection of artificial intelligence (AI) and conversational data offers promising oppor- tunities for advancing research in specialized fields such as biology and health sciences. The WildChat dataset, comprising over one million user-ChatGPT interactions, serves as a valuable resource for analyzing how advanced language models engage with complex topics. This work aims to explore how conversational AI models interpret and manage bioinformatics-related queries, assessing their… See the full description on the dataset page: https://huggingface.co/datasets/david4096/wildbio.

  17. h

    ChatGPT-RealUser-2.2M-preview

    • huggingface.co
    Updated Aug 30, 2025
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    Gata (2025). ChatGPT-RealUser-2.2M-preview [Dataset]. https://huggingface.co/datasets/Gata-community/ChatGPT-RealUser-2.2M-preview
    Explore at:
    Dataset updated
    Aug 30, 2025
    Dataset authored and provided by
    Gata
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    ChatGPT-RealUser-2.2M: A Large-Scale Dataset of Real-User, Real-World ChatGPT Conversations

    ChatGPT-RealUser-2.2M is a large-scale dataset of real-user, Real-World ChatGPT conversations developed by Gata. From 2024–2025, participants using Gata’s GPT-to-Earn product opted in to share their chats and earned points based on conversation quality. The dataset covers GPT-3.5, GPT-4, and o1 models, and contains 2,244,389 conversations from 15,316 unique users. Because many chats are… See the full description on the dataset page: https://huggingface.co/datasets/Gata-community/ChatGPT-RealUser-2.2M-preview.

  18. h

    ShareGPT52K

    • huggingface.co
    Updated Apr 5, 2023
    + more versions
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    Ryoko AI (2023). ShareGPT52K [Dataset]. https://huggingface.co/datasets/RyokoAI/ShareGPT52K
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 5, 2023
    Dataset authored and provided by
    Ryoko AI
    License

    https://choosealicense.com/licenses/cc0-1.0/https://choosealicense.com/licenses/cc0-1.0/

    Description

    Dataset Card for ShareGPT52K90K

      Dataset Summary
    

    This dataset is a collection of approximately 52,00090,000 conversations scraped via the ShareGPT API before it was shut down. These conversations include both user prompts and responses from OpenAI's ChatGPT. This repository now contains the new 90K conversations version. The previous 52K may be found in the old/ directory.

      Supported Tasks and Leaderboards
    

    text-generation

      Languages
    

    This dataset is… See the full description on the dataset page: https://huggingface.co/datasets/RyokoAI/ShareGPT52K.

  19. WildChat-1M

    • huggingface.co
    Updated Jul 22, 2024
    + more versions
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    Ai2 (2024). WildChat-1M [Dataset]. https://huggingface.co/datasets/allenai/WildChat-1M
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 22, 2024
    Dataset provided by
    Allen Institute for AIhttp://allenai.org/
    Authors
    Ai2
    License

    https://choosealicense.com/licenses/odc-by/https://choosealicense.com/licenses/odc-by/

    Description

    Dataset Card for WildChat

      Dataset Description
    

    Paper: https://arxiv.org/abs/2405.01470

    Interactive Search Tool: https://wildvisualizer.com (paper)

    License: ODC-BY

    Language(s) (NLP): multi-lingual

    Point of Contact: Yuntian Deng

      Dataset Summary
    

    WildChat is a collection of 1 million conversations between human users and ChatGPT, alongside demographic data, including state, country, hashed IP addresses, and request headers. We collected WildChat by… See the full description on the dataset page: https://huggingface.co/datasets/allenai/WildChat-1M.

  20. WildChat

    • huggingface.co
    Updated Jul 23, 2024
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    Ai2 (2024). WildChat [Dataset]. https://huggingface.co/datasets/allenai/WildChat
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 23, 2024
    Dataset provided by
    Allen Institute for AIhttp://allenai.org/
    Authors
    Ai2
    License

    https://choosealicense.com/licenses/odc-by/https://choosealicense.com/licenses/odc-by/

    Description

    Dataset Card for WildChat

      Note: a newer version with 4.8 million conversations and demographic information can be found here.
    
    
    
    
    
      Dataset Description
    

    Paper: https://arxiv.org/abs/2405.01470

    Interactive Search Tool: https://wildvisualizer.com (paper)

    License: ODC-BY

    Language(s) (NLP): multi-lingual

    Point of Contact: Yuntian Deng

      Dataset Summary
    

    WildChat is a collection of 650K conversations between human users and ChatGPT. We collected WildChat… See the full description on the dataset page: https://huggingface.co/datasets/allenai/WildChat.

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Express Legal Funding (2025). ChatGPT Usage by U.S. Census Region – Survey Data [Dataset]. https://expresslegalfunding.com/chatgpt-study/

ChatGPT Usage by U.S. Census Region – Survey Data

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2 scholarly articles cite this dataset (View in Google Scholar)
htmlAvailable download formats
Dataset updated
Sep 10, 2025
Dataset authored and provided by
Express Legal Funding
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Variables measured
Pacific, Mountain, New England, South Atlantic, Middle Atlantic, East North Central, East South Central, West North Central, West South Central
Description

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.

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