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| Empirical Study and Construction of a User Privacy Paradox Behavior Portrait Model in Human-AI Interaction Scenarios |
| Mao Taitian, Tang Gan, Zhou Zhizhen |
| School of Public Administration, Xiangtan University, Xiangtan 411105 |
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Abstract To explore the causal factors and behavioral outcomes of users' privacy paradox behavior in human-artificial intelligence (AI) interaction contexts, this study aimed to develop a model for user privacy paradox behavior and conduct persona analysis. This research provides theoretical support for optimizing user experience and formulating privacy protection policies. A combination of online surveys and semi-structured interviews was used along with grounded theory, to extract the key factors. Based on the stressor-strain-outcome (SSO) and information ecology theories, this study constructed a persona model of privacy paradox behavior in human-AI interaction contexts. Through a K-means clustering analysis of the survey data, four distinct persona types were identified: proactive explorers, cautious defenders, rational balancers, and passive avoiders. These findings offer comprehensive insight into the privacy paradox behavior types of users on AI-generated content platforms.
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Received: 17 October 2024
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