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| Format: | Preprint |
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2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2306.12951 |
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| _version_ | 1866909105280516096 |
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| author | Koonchanok, Ratanond Pan, Yanling Jang, Hyeju |
| author_facet | Koonchanok, Ratanond Pan, Yanling Jang, Hyeju |
| contents | 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 occupations in arts and entertainment tweeted aboutChatGPT most frequently. Additionally, people tended to tweet about topics relevant to their occupation. For instance, Cybersecurity is the most discussed topic among those with occupations related to computer and math, and Education is the most discussed topic among those in academic and research. Overall, our exploratory study provides insights into the public perception of ChatGPT, which could be valuable to both the general public and developers of this technology. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_12951 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Public Attitudes Toward ChatGPT on Twitter: Sentiments, Topics, and Occupations Koonchanok, Ratanond Pan, Yanling Jang, Hyeju Computation and Language 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 occupations in arts and entertainment tweeted aboutChatGPT most frequently. Additionally, people tended to tweet about topics relevant to their occupation. For instance, Cybersecurity is the most discussed topic among those with occupations related to computer and math, and Education is the most discussed topic among those in academic and research. Overall, our exploratory study provides insights into the public perception of ChatGPT, which could be valuable to both the general public and developers of this technology. |
| title | Public Attitudes Toward ChatGPT on Twitter: Sentiments, Topics, and Occupations |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2306.12951 |