Human-Computer Interaction (SIG HCI)
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Paper Type
Complete
Paper Number
1330
Description
By leveraging recent advancements in affective computing, emotion-based personalization systems provide media offerings tailored to users’ emotions. Although emotionally intelligent systems increasingly attract attention both in research and in practice, research on users’ perceptions of emotion-based personalization is sparse. Building on the personalization-privacy trade-off, I propose a comprehensive framework to investigate how the use of affective technologies for personalization impacts users’ trust mediated by their perceived benefits and threats. To test the research model, I conduct an experiment with a fictitious music personalization system and analyze the results using partial least squares structural equation modeling. The results show that emotion-based personalization positively impacts users’ trust via perceived emotional support but simultaneously hampers trust via privacy concerns and emotional creepiness.
Recommended Citation
Thürmel, Verena, "I Know How You Feel: An Investigation of Users’ Trust in Emotion-Based Personalization Systems" (2021). AMCIS 2021 Proceedings. 9.
https://aisel.aisnet.org/amcis2021/sig_hci/sig_hci/9
I Know How You Feel: An Investigation of Users’ Trust in Emotion-Based Personalization Systems
By leveraging recent advancements in affective computing, emotion-based personalization systems provide media offerings tailored to users’ emotions. Although emotionally intelligent systems increasingly attract attention both in research and in practice, research on users’ perceptions of emotion-based personalization is sparse. Building on the personalization-privacy trade-off, I propose a comprehensive framework to investigate how the use of affective technologies for personalization impacts users’ trust mediated by their perceived benefits and threats. To test the research model, I conduct an experiment with a fictitious music personalization system and analyze the results using partial least squares structural equation modeling. The results show that emotion-based personalization positively impacts users’ trust via perceived emotional support but simultaneously hampers trust via privacy concerns and emotional creepiness.
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