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Schneegass, Stefan; Poguntke, Romina; Machulla, Tonja (2019): Understanding the Impact of Information Representation on Willingness to Share Information. In: Chi 2019: Proceedings of the 2019 Chi Conference on Human Factors in Computing Systems
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Since the release of the first activity tracker, there has been a steady increase in the number of sensors embedded in wearable devices and with it in the amount and diversity of information that can be derived from these sensors. This development leads to novel privacy threats for users. In a web survey with 248 participants, we explored whether users' willingness to share private data is dependent on how the data is requested by an application. Specifically, requests can be formulated as access to sensor data or as access to information derived from the sensor data (e.g., accelerometer vs. sleep quality). We show that non-expert users lack an understanding of how the two representation levels relate to each other. The results suggest that the willingness to share sensor data over derived information is governed by whether the derived information has positive or negative connotations (e. g., training intensity vs. life expectancy). Using the results of the survey, we derive implications for supporting users in protecting their private data collected via wearable sensors.