ArticleInternational journal of human-computer interaction2025
Exploring the Early Adoption of Open AI among Laypeople and Technical Professionals: An Analysis of Twitter Conversations on #ChatGPT and #GPT3.
Article in International journal of human-computer interaction, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Decision-Making Dilemmas Among Elderly Prostate Cancer Patients ReceivingPatient preference and adherence · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Large language models (LLMs) such as GPT-3 and their derivative products such as ChatGPT have garnered significant attention for their remarkable ability to process texts and conduct human-like conversations. Guided by the Diffusion of Innovation theory, this study examines the early discussions about LLMs on Twitter, specifically about ChatGPT and GPT-3, during the first three months following the release of ChatGPT. By utilizing topic structural modeling and sentiment analysis on a sample of 42,273 #ChatGPT tweets and 17,639 #GPT3 tweets, we explore how laypeople and technical professionals differ in their attitudes in the early stage of the adoption of LLMs. Our findings suggest that the discussion surrounding ChatGPT and GPT-3 primarily revolves around relative advantage and compatibility, with the majority of #ChatGPT conversations demonstrating negative sentiment and #GPT3 discussions containing more positive topics. The Twitter discussion using #ChatGPT is highly business-oriented, while the discussion of #GPT3 covers a broader range of topics in terms of the characteristics, applications, and potential ethical concerns of LLMs. This study offers implications for government agencies and policymakers, suggesting that further research is needed to fully understand the potential applications and risks of LLMs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.