Data sharing has become prevalent with the rapid growth of mobile technologies. A lack of awareness and understanding of privacy practices often results in the installation of privacy-invasive applications (apps) which could potentially put users' personal data at risk. This study aimed to explore how users’ risk perception could be shifted towards more privacy-aware decisions through generation fluency and framing manipulations. It is an online study composed of three components, an experiment and two questionnaires. We manipulated the availability of privacy worries, by asking participants to generate either 2 or 10 privacy worries. Generating 10 worries was experienced as difficult, whereas generating 2 was easy. The difficult experience led to downgraded perception of risk, and consequently increased likelihood of installing a low privacy rated fictional app. Therefore, we suggest that improving generation fluency of privacy concerns could encourage users’ adoption of a more conservative judgment strategy when installing an app, safeguarding them against privacy-invasive apps.

随着移动技术的迅速发展，数据共享已变得越来越普遍。缺乏对隐私惯例的了解和理解通常会导致安装隐私入侵应用程序，从而可能使用户的个人数据面临风险。这项研究旨在探讨如何通过一代流利度和框架操纵将用户的风险感知转变为更具隐私意识的决策。这是一个在线研究，由三个部分，一个实验和两个调查表组成。通过要求参与者产生2或10个隐私担忧，我们操纵了隐私担忧的可用性。产生10个担忧很困难，而产生2个则很容易。艰难的经历导致人们对风险的看法降低了，因此增加了安装低隐私等级的虚构应用的可能性。因此，我们建议提高隐私问题的生成流畅度可以鼓励用户在安装应用程序时采取更为保守的判断策略，以保护他们免受侵犯隐私的应用程序的侵害。