Behavior of Social Network Users to Privacy Leakage: An Agent-Based Approach

Kaiyang Li, Guangchun Luo, Huaigu Wu, Chunyu Wang

Abstract: As the rapid development of online social networks, the service providers collect a tremendous amount of personal data. They have the potential motivation to sell the users’ data for extra profits. To figure out the trading strategy of the service providers, we should understand the users’ behavior after they realized privacy leaked. In this paper, we build the users’ utility function and information diffusion model about privacy leakage. We take advantage of agent-based model to simulate the evolution of online social network after privacy leaked. Our result shows the service providers are almost certain to sell some personal data. If users are very attention to their privacy, the service providers more likely sell all the data.