PUB - Publikationen an der Universität Bielefeld

Social interactions strongly affect both physical and mental health. However, measuring this impact in an objective, unobtrusive and ethical manner presents a challenge. To overcome this challenge, we introduce Dona, an online platform, which allows individuals to donate retrospective messaging data from WhatsApp and Facebook. Participants first request their data from messaging services. Then the data is anonymized on their devices by replacing names with IDs and messages by wordcounts, while preserving timestamps. In the final step, participants submit their donations and complete study-specific questionnaires. The donated data offers multiple benefits for participants, healthcare providers and researchers. In particular, the participants receive visualizations of their messaging behavior as a reward for their donation. They can share these visualizations with healthcare providers for quantitative monitoring of their social interactions. This can be beneficial for the early identification of changes that may signal health risks, such as social withdrawal or excessive messaging behavior. Finally, researchers can use the anonymized data in large-scale machine-learning analyses to identify patterns of social interactions associated with different health outcomes. Ultimately, Dona offers a promising opportunity to leverage modern technologies to better understand the impact of social interactions on health.