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Engagement in proactive recommendations: The role of recommendation accuracy, information privacy concerns and personality traits

机译:积极参与推荐:推荐准确性,信息隐私问题和人格特质的作用

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摘要

The present research explored to what extent user engagement in proactive recommendation scenarios is influenced by the accuracy of recommendations, concerns with information privacy, and trait personality. We hypothesized that people's self-reported information privacy concerns would matter more when they received accurate (vs. inaccurate) proactive recommendations, because these pieces of advice would seem fair to them. We further hypothesized that this would particularly be the case for people high on the social personality trait Extraversion, who are by inclination prone to behaving in a more socially engaging manner. We put this to the test in a controlled experiment, in which users received manipulated proactive recommendations of high or low accuracy on their smartphone. Results indicated that information privacy concerns positively influenced a user's engagement with proactive recommendations. Recommendation accuracy influenced user engagement in interaction with information privacy concerns and personality traits. Implications for the design of human-computer interaction for recommender systems are addressed.
机译:本研究探讨了在何种程度上用户参与主动推荐场景会受到推荐准确性,对信息隐私的关注以及特质个性的影响。我们假设人们在收到准确的(相对于不准确的)积极主动的建议时,人们自我报告的信息隐私问题会变得更加重要,因为这些建议对他们而言似乎很公平。我们进一步假设,对于那些具有较高社交个性特征“外向性”的人而言,情况尤其如此,他们倾向于以更具社会参与性的方式表现。我们在一个受控实验中对此进行了测试,在该实验中,用户在其智能手机上收到了对准确性高或低的操纵性主动建议。结果表明,信息隐私问题对用户对主动建议的参与产生了积极影响。推荐准确性影响用户参与信息隐私问题和个性特征的互动。解决了对推荐系统人机交互设计的影响。

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