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Service-centric Networking2019-06-21 What data are smartphone users willing to share with researchers? – Read our new research article online


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What data are smartphone users willing to share with researchers? – Read our new research article online

The Journal of Ambient Intelligence and Humanized Computing (JAIHC) published our manuscript “What data are smartphone users willing to share with researchers? Designing and evaluating a privacy model for mobile data collection apps.” In the paper, Felix Beierle and his co-authors develop a privacy model for mobile apps related to data collection. They further analyze data collected from the Android app TYDR in order to analyze what data users are willing to share. Younger users tend to be less willing to enable all Android system permissions and share their data. Male users of TYDR were more willing to share their data than female users.

The paper is available to read here.

The work was done in the context of our research project TYDR, in collaboration with researchers from computer science and psychology from Germany, Austria, and Switzerland.


Context-aware applications stemming from diverse fields like mobile health, recommender systems, and mobile commerce potentially benefit from knowing aspects of the user’s personality. As filling out personality questionnaires is tedious, we propose the prediction of the user’s personality from smartphone sensor and usage data. In order to collect data for researching the relationship between smartphone data and personality, we developed the Android app track your daily routine (TYDR), which tracks and records smartphone data and utilizes psychometric personality questionnaires. With TYDR, we track a larger variety of smartphone data than many other existing apps, including metadata on notifications, photos taken, and music played back by the user. Based on the development of TYDR, we introduce a general context data model consisting of four categories that focus on the user’s different types of interactions with the smartphone: physical conditions and activity, device status and usage, core functions usage, and app usage. On top of this, we developed the Privacy Model for Mobile Data Collection Applications (PM-MoDaC) specifically tailored for apps that are related to the collection of mobile data, consisting of nine proposed privacy measures. We present the implementation of all of those measures in TYDR. Our experimental evaluation is based on data collected with TYDR during a two-month period. We find evidence that our users accept our proposed privacy model. Based on data about granting TYDR all or no Android system permissions, we find evidence that younger users tend to be less willing to share their data (average age of 30 years compared to 35 years). We also observe that female users tend to be less willing to share data compared to male users. We did not find any evidence that education or personality traits are a factor related to data sharing. TYDR users score higher on the personality trait openness to experience than the average of the population, which we assume to be evidence that the type of app influences the user base it attracts in terms of average personality traits.



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