Public Attitudes Toward ChatGPT on Twitter: Sentiments, Topics, and Occupations
Ratanond Koonchanok, Yanling Pan, Hyeju Jang

TL;DR
This study analyzes Twitter discussions on ChatGPT from late 2022 to mid-2023, revealing largely positive sentiments, key discussion topics, and occupation-based differences in conversations about the AI chatbot.
Contribution
It applies NLP techniques to Twitter data to explore public attitudes, topics, and occupational differences related to ChatGPT, providing new insights into societal perceptions.
Findings
Overall sentiment was neutral to positive, decreasing negative sentiments over time.
Main discussion topics included Education, Bard, Search Engines, and Cybersecurity.
Arts and entertainment users tweeted most frequently about ChatGPT.
Abstract
ChatGPT sets a new record with the fastest-growing user base, as a chatbot powered by a large language model (LLM). While it demonstrates state-of-the-art capabilities in a variety of language-generation tasks, it also raises widespread public concerns regarding its societal impact. In this paper, we investigated public attitudes towards ChatGPT by applying natural language processing techniques such as sentiment analysis and topic modeling to Twitter data from December 5, 2022 to June 10, 2023. Our sentiment analysis result indicates that the overall sentiment was largely neutral to positive, and negative sentiments were decreasing over time. Our topic model reveals that the most popular topics discussed were Education, Bard, Search Engines, OpenAI, Marketing, and Cybersecurity, but the ranking varies by month. We also analyzed the occupations of Twitter users and found that those with…
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Taxonomy
TopicsSentiment Analysis and Opinion Mining · Topic Modeling · Computational and Text Analysis Methods
