Who Is Spreading AI-Generated Health Rumors? A Study on the Association Between AIGC Interaction Types and the Willingness to Share Health Rumors
Generative chatbots based on artificial intelligence technology have become an essential channel for people to obtain health information. They provide not only comprehensive health information but also real-time virtual companionship. However, the health information provided by AI may not be complet...
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2025-02-01
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| Series: | Social Media + Society |
| Online Access: | https://doi.org/10.1177/20563051251323391 |
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| author | Zehang Xie |
| author_facet | Zehang Xie |
| author_sort | Zehang Xie |
| collection | DOAJ |
| description | Generative chatbots based on artificial intelligence technology have become an essential channel for people to obtain health information. They provide not only comprehensive health information but also real-time virtual companionship. However, the health information provided by AI may not be completely accurate. Employing a 3 × 2 × 2 experimental design, the research examines the effects of interaction types with AI-generated content (AIGC), specifically under virtual companionship and knowledge acquisition scenarios, on the willingness to share health-related rumors. In addition, it explores the impact of the nature of the rumors (fear vs hope) and the role of altruistic tendencies in this context. The results show that people are more willing to share rumors in a knowledge acquisition situation. Fear-type rumors can stimulate people’s willingness to share more than hope-type rumors. Altruism plays a moderating role, increasing the willingness to share health rumors in the scenario of virtual companionship, while decreasing the willingness to share health rumors in the scenario of knowledge acquisition. These findings support Kelley’s three-dimensional attribution theory and negativity bias theory, and extend these results to the field of human–computer interaction. The results of this study help to understand the rumor spreading mechanism in the context of human–computer interaction and provide theoretical support for the improvement of health chatbots. |
| format | Article |
| id | doaj-art-8a81c56b0d874929b6d0c9cc3e4e8a03 |
| institution | DOAJ |
| issn | 2056-3051 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Social Media + Society |
| spelling | doaj-art-8a81c56b0d874929b6d0c9cc3e4e8a032025-08-20T02:45:24ZengSAGE PublishingSocial Media + Society2056-30512025-02-011110.1177/20563051251323391Who Is Spreading AI-Generated Health Rumors? A Study on the Association Between AIGC Interaction Types and the Willingness to Share Health RumorsZehang XieGenerative chatbots based on artificial intelligence technology have become an essential channel for people to obtain health information. They provide not only comprehensive health information but also real-time virtual companionship. However, the health information provided by AI may not be completely accurate. Employing a 3 × 2 × 2 experimental design, the research examines the effects of interaction types with AI-generated content (AIGC), specifically under virtual companionship and knowledge acquisition scenarios, on the willingness to share health-related rumors. In addition, it explores the impact of the nature of the rumors (fear vs hope) and the role of altruistic tendencies in this context. The results show that people are more willing to share rumors in a knowledge acquisition situation. Fear-type rumors can stimulate people’s willingness to share more than hope-type rumors. Altruism plays a moderating role, increasing the willingness to share health rumors in the scenario of virtual companionship, while decreasing the willingness to share health rumors in the scenario of knowledge acquisition. These findings support Kelley’s three-dimensional attribution theory and negativity bias theory, and extend these results to the field of human–computer interaction. The results of this study help to understand the rumor spreading mechanism in the context of human–computer interaction and provide theoretical support for the improvement of health chatbots.https://doi.org/10.1177/20563051251323391 |
| spellingShingle | Zehang Xie Who Is Spreading AI-Generated Health Rumors? A Study on the Association Between AIGC Interaction Types and the Willingness to Share Health Rumors Social Media + Society |
| title | Who Is Spreading AI-Generated Health Rumors? A Study on the Association Between AIGC Interaction Types and the Willingness to Share Health Rumors |
| title_full | Who Is Spreading AI-Generated Health Rumors? A Study on the Association Between AIGC Interaction Types and the Willingness to Share Health Rumors |
| title_fullStr | Who Is Spreading AI-Generated Health Rumors? A Study on the Association Between AIGC Interaction Types and the Willingness to Share Health Rumors |
| title_full_unstemmed | Who Is Spreading AI-Generated Health Rumors? A Study on the Association Between AIGC Interaction Types and the Willingness to Share Health Rumors |
| title_short | Who Is Spreading AI-Generated Health Rumors? A Study on the Association Between AIGC Interaction Types and the Willingness to Share Health Rumors |
| title_sort | who is spreading ai generated health rumors a study on the association between aigc interaction types and the willingness to share health rumors |
| url | https://doi.org/10.1177/20563051251323391 |
| work_keys_str_mv | AT zehangxie whoisspreadingaigeneratedhealthrumorsastudyontheassociationbetweenaigcinteractiontypesandthewillingnesstosharehealthrumors |