Name
Title | ||
|---|---|---|
Investigating Simple Privacy Indicators for Supporting Users when Installing New Mobile Apps |
Abstract | ||
|---|---|---|
BSTRACT Mobile devices have become daily companions for millions of users. They have access to privacy-sensitive data about their users which stresses the importance of privacy. Users have to make privacy-related decisions already before app installation because once installed, apps can access potential privacy-sensitive data. In this work-in-progress, we present an in-depth investigation of privacy indicator visualizations for mobile app stores. We report the results of two consecutive user studies in which we investigate 1) visual depiction, 2) score, and 3) monetary value of collected data. Our studies reveal that a visual depiction by a privacy meter were easiest to understand for users, scores were easiest to spot, and monetary value was most difficult to interpret and requires further investigation. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3411763.3451791 | Conference on Human Factors in Computing Systems |
Keywords | DocType | Citations |
information privacy, privacy indicator, mobile privacy | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alina Stöver | 1 | 1 | 1.70 |
| Nina Gerber | 2 | 5 | 9.21 |
| Sushma Kaushik | 3 | 0 | 0.34 |
| Max Mühlhäuser | 4 | 1652 | 252.87 |
| Karola Marky | 5 | 11 | 12.34 |