An Agent-Based Approach to Model the Proliferation of Personal Data

Today's Internet on the one hand shows an increasing number of web systems and social networks that gather and exchange personal data. On the other hand a significant fraction of users has a lack of understanding of the unintended side effects caused by the dissemination of their personal data. Hence, we modeled and simulated the data proliferation, i.e., the interaction of humans and web systems and the resulting data flows between them. Our objective is to find quantitative measures like the market value of personal data to assess such proliferation scenarios and appropriately visualize the effects to users. Therefore, we make use of an agent-based model to emulate behavior and strategy of users, systems, and information gatherers and hunters. Our simulations, based on Repast Symphony, allow a comparison between various behavioral patterns of user groups and between several systems to curb the data proliferation.