Academic Journal
A pilot study of measuring emotional response and perception of LLM-generated questionnaire and human-generated questionnaires
| Title: | A pilot study of measuring emotional response and perception of LLM-generated questionnaire and human-generated questionnaires |
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| Authors: | Zhao Zou, Omar Mubin, Fady Alnajjar, Luqman Ali |
| Source: | Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024) |
| Publisher Information: | Nature Portfolio, 2024. |
| Publication Year: | 2024 |
| Collection: | LCC:Medicine LCC:Science |
| Subject Terms: | Medicine, Science |
| More Details: | Abstract The advent of ChatGPT has sparked a heated debate surrounding natural language processing technology and AI-powered chatbots, leading to extensive research and applications across various disciplines. This pilot study aims to investigate the impact of ChatGPT on users' experiences by administering two distinct questionnaires, one generated by humans and the other by ChatGPT, along with an Emotion Detecting Model. A total of 14 participants (7 female and 7 male) aged between 18 and 35 years were recruited, resulting in the collection of 8672 ChatGPT-associated data points and 8797 human-associated data points. Data analysis was conducted using Analysis of Variance (ANOVA). The results indicate that the utilization of ChatGPT enhances participants' happiness levels and reduces their sadness levels. While no significant gender influences were observed, variations were found about specific emotions. It is important to note that the limited sample size, narrow age range, and potential cultural impacts restrict the generalizability of the findings to a broader population. Future research directions should explore the impact of incorporating additional language models or chatbots on user emotions, particularly among specific age groups such as older individuals and teenagers. As one of the pioneering works evaluating the human perception of ChatGPT text and communication, it is noteworthy that ChatGPT received positive evaluations and demonstrated effectiveness in generating extensive questionnaires. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2045-2322 |
| Relation: | https://doaj.org/toc/2045-2322 |
| DOI: | 10.1038/s41598-024-53255-1 |
| Access URL: | https://doaj.org/article/d4518c76740446ccb484f76a34505db3 |
| Accession Number: | edsdoj.4518c76740446ccb484f76a34505db3 |
| Database: | Directory of Open Access Journals |
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| ISSN: | 20452322 |
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| DOI: | 10.1038/s41598-024-53255-1 |
| Published in: | Scientific Reports |
| Language: | English |