Reasoning about privacy in mobile application install decisions: Risk perception and framing

Siok Wah Tay, Pin Shen Teh, Stephen Payne

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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.
Original languageEnglish
Article number102517
JournalInternational Journal of Human-Computer Studies
Early online date21 Jul 2020
Publication statusPublished - 1 Jan 2021


  • Privacy; mobile application; generation fluency; risk perception; framing; decision-making


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