From ChatGPT to Sora: Analyzing Public Opinions and Attitudes on Generative Artificial Intelligence in Social Media
This study examines public opinions, emotional tendencies, and psychological linguistic characteristics associated with the launch of OpenAI’s ChatGPT and the advanced video generation model, Sora, by analyzing discussions on the Chinese social media platform Weibo. A total of 24,727 vali...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10843672/ |
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| author | Wenyan Feng Yuhang Li Chunhao Ma Lisai Yu |
| author_facet | Wenyan Feng Yuhang Li Chunhao Ma Lisai Yu |
| author_sort | Wenyan Feng |
| collection | DOAJ |
| description | This study examines public opinions, emotional tendencies, and psychological linguistic characteristics associated with the launch of OpenAI’s ChatGPT and the advanced video generation model, Sora, by analyzing discussions on the Chinese social media platform Weibo. A total of 24,727 valid user-generated texts (1,762,296 words) were collected and analyzed using Python and its associated APIs. Word co-occurrence network analysis, topic modeling based on Latent Dirichlet Allocation (LDA), and emotional characteristics based on the DLUT Emotion Ontology and psycholinguistic analyses based on the Linguistic Inquiry and Word Count (LIWC) dictionary were employed to explore public views on these generative AI technologies. The findings reveal a shift in public focus over time, from initial excitement about technological advancements to growing interest in commercialization, labor, education, ethics, and global competition. The public’s emotional responses to AI were a mix of excitement and apprehension. The study identifies seven distinct emotional types, providing a nuanced understanding of public psychological reactions, which contrasts with previous binary classifications. This research contributes valuable insights for policymakers, businesses, and researchers, highlighting the public’s evolving acceptance of generative AI technologies. |
| format | Article |
| id | doaj-art-1428e458b4cb45b5868483667e040c31 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-1428e458b4cb45b5868483667e040c312025-01-25T00:02:17ZengIEEEIEEE Access2169-35362025-01-0113144851449810.1109/ACCESS.2025.353068310843672From ChatGPT to Sora: Analyzing Public Opinions and Attitudes on Generative Artificial Intelligence in Social MediaWenyan Feng0https://orcid.org/0009-0009-9616-5929Yuhang Li1https://orcid.org/0000-0003-2635-0212Chunhao Ma2https://orcid.org/0000-0001-6846-3608Lisai Yu3https://orcid.org/0009-0004-6380-2956Zhijiang College, Zhejiang University of Technology, Shaoxing, ChinaZhijiang College, Zhejiang University of Technology, Shaoxing, ChinaDepartment of Railroad Construction Services, China Railway Materials Tianjin Company Ltd., Tianjin, ChinaCenter for the Study of Language and Cognition, Zhejiang University, Hangzhou, ChinaThis study examines public opinions, emotional tendencies, and psychological linguistic characteristics associated with the launch of OpenAI’s ChatGPT and the advanced video generation model, Sora, by analyzing discussions on the Chinese social media platform Weibo. A total of 24,727 valid user-generated texts (1,762,296 words) were collected and analyzed using Python and its associated APIs. Word co-occurrence network analysis, topic modeling based on Latent Dirichlet Allocation (LDA), and emotional characteristics based on the DLUT Emotion Ontology and psycholinguistic analyses based on the Linguistic Inquiry and Word Count (LIWC) dictionary were employed to explore public views on these generative AI technologies. The findings reveal a shift in public focus over time, from initial excitement about technological advancements to growing interest in commercialization, labor, education, ethics, and global competition. The public’s emotional responses to AI were a mix of excitement and apprehension. The study identifies seven distinct emotional types, providing a nuanced understanding of public psychological reactions, which contrasts with previous binary classifications. This research contributes valuable insights for policymakers, businesses, and researchers, highlighting the public’s evolving acceptance of generative AI technologies.https://ieeexplore.ieee.org/document/10843672/Generative artificial intelligenceChatGPTsoratopic modelingsentiment analysispsycholinguistics |
| spellingShingle | Wenyan Feng Yuhang Li Chunhao Ma Lisai Yu From ChatGPT to Sora: Analyzing Public Opinions and Attitudes on Generative Artificial Intelligence in Social Media IEEE Access Generative artificial intelligence ChatGPT sora topic modeling sentiment analysis psycholinguistics |
| title | From ChatGPT to Sora: Analyzing Public Opinions and Attitudes on Generative Artificial Intelligence in Social Media |
| title_full | From ChatGPT to Sora: Analyzing Public Opinions and Attitudes on Generative Artificial Intelligence in Social Media |
| title_fullStr | From ChatGPT to Sora: Analyzing Public Opinions and Attitudes on Generative Artificial Intelligence in Social Media |
| title_full_unstemmed | From ChatGPT to Sora: Analyzing Public Opinions and Attitudes on Generative Artificial Intelligence in Social Media |
| title_short | From ChatGPT to Sora: Analyzing Public Opinions and Attitudes on Generative Artificial Intelligence in Social Media |
| title_sort | from chatgpt to sora analyzing public opinions and attitudes on generative artificial intelligence in social media |
| topic | Generative artificial intelligence ChatGPT sora topic modeling sentiment analysis psycholinguistics |
| url | https://ieeexplore.ieee.org/document/10843672/ |
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