mlsanityData to 14 Oct 2026

"I think this is the most disruptive technology": Exploring Sentiments of ChatGPT Early Adopters using Twitter Data

arXiv 2212.05856 ↗First posted 12 Dec 2022cs.CLcited by 32

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Abstract (arXiv)

Large language models have recently attracted significant attention due to their impressive performance on a variety of tasks. ChatGPT developed by OpenAI is one such implementation of a large, pre-trained language model that has gained immense popularity among early adopters, where certain users go to the extent of characterizing it as a disruptive technology in many domains. Understanding such early adopters' sentiments is important because it can provide insights into the potential success or failure of the technology, as well as its strengths and weaknesses. In this paper, we conduct a mixed-method study using 10,732 tweets from early ChatGPT users. We first use topic modelling to identify the main topics and then perform an in-depth qualitative sentiment analysis of each topic. Our results show that the majority of the early adopters have expressed overwhelmingly positive sentiments related to topics such as Disruptions to software development, Entertainment and exercising creativity. Only a limited percentage of users expressed concerns about issues such as the potential for misuse of ChatGPT, especially regarding topics such as Impact on educational aspects. We discuss these findings by providing specific examples for each topic and then detail implications related to addressing these concerns for both researchers and users.

Key facts. Cited by 32 papers in the map (data through 14 Oct 2026). Builds on 3 of its 35 references that are in the map. First posted on arXiv 12 Dec 2022.

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3 of 35 references.

References · 3

  1. 2020Challenges in Docker Development: A Large-scale Study Using Stack Overflowcited by 3
  2. 2022APIRO: A Framework for Automated Security Tools API Recommendationcited by 3
  3. 2022Collaborative Application Security Testing for DevSecOps: An Empirical Analysis of Challenges, Best Practices and Tool Supportcited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 20; 2024: 6; 2025: 3; 2026: 3.

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  1. 2023Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Modelscited by 154
  2. 2023Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulnesscited by 130
  3. 2023Generative Pre-trained Transformer: A Comprehensive Review on Enabling Technologies, Potential Applications, Emerging Challenges, and Future Directionscited by 55
  4. 2023ChatGPT and a New Academic Reality: Artificial Intelligence-Written Research Papers and the Ethics of the Large Language Models in Scholarly Publishingcited by 52
  5. 2023ChatGPT: A Meta-Analysis after 2.5 Monthscited by 51
  6. 2023An Empirical Study on Information Extraction using Large Language Modelscited by 46
  7. 2023LLM-assisted Knowledge Graph Engineering: Experiments with ChatGPTcited by 42
  8. 2023Bias and Fairness in Chatbots: An Overviewcited by 20
  9. 2023ChatAgri: Exploring Potentials of ChatGPT on Cross-linguistic Agricultural Text Classificationcited by 14
  10. 2023Multidimensional Evaluation for Text Style Transfer Using ChatGPTcited by 12
  11. 2024ChatNVD: Advancing Cybersecurity Vulnerability Assessment with Large Language Modelscited by 11
  12. 2023Conversational AI-Powered Design: ChatGPT as Designer, User, and Productcited by 8
20 more
  1. 2023Seeing ChatGPT Through Students' Eyes: An Analysis of TikTok Datacited by 7
  2. 2025RegimeFolio: A Regime Aware ML System for Sectoral Portfolio Optimization in Dynamic Marketscited by 7
  3. 2023Public Attitudes Toward ChatGPT on Twitter: Sentiments, Topics, and Occupationscited by 6
  4. 2023Learning to Prompt in the Classroom to Understand AI Limits: A pilot studycited by 6
  5. 2023ChatGPT v Bard v Bing v Claude 2 v Aria v human-expert. How good are AI chatbots at scientific writing?cited by 6
  6. 2024The Battle of LLMs: A Comparative Study in Conversational QA Taskscited by 5
  7. 2024Rise of Generative Artificial Intelligence in Sciencecited by 5
  8. 2023ChatGPT-Crawler: Find out if ChatGPT really knows what it's talking aboutcited by 3
  9. 2025EmoXpt: Analyzing Emotional Variances in Human Comments and LLM-Generated Responsescited by 3
  10. 2024AI Insights: A Case Study on Utilizing ChatGPT Intelligence for Research Paper Analysiscited by 2
  11. 2024A Qualitative Study on Using ChatGPT for Software Security: Perception vs. Practicalitycited by 2
  12. 2026AgenticVM: Agentic AI for Adaptive Software Vulnerability Managementcited by 2
  13. 2023Exploring the Cognitive Dynamics of Artificial Intelligence in the Post-COVID-19 and Learning 3.0 Era: A Case Study of ChatGPTcited by 1
  14. 2023What Types of Questions Require Conversation to Answer? A Case Study of AskReddit Questionscited by 1
  15. 2023Leveraging Explainable AI to Analyze Researchers' Aspect-Based Sentiment about ChatGPTcited by 1
  16. 2025Winning and losing with Artificial Intelligence: What public discourse about ChatGPT tells us about how societies make sense of technological changecited by 1
  17. 2026Evaluating ChatGPT on Medical Information Extraction Tasks: Performance, Explainability and Beyondcited by 1
  18. 2026Comparative Analysis of Large Language Models in Healthcarecited by 1
  19. 2023Mapping ChatGPT in Mainstream Media to Unravel Jobs and Diversity Challenges: Early Quantitative Insights through Sentiment Analysis and Word Frequency Analysiscited by 0
  20. 2024How much reliable is ChatGPT's prediction on Information Extraction under Input Perturbations?cited by 0

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