Modeling human dynamics with adaptive interest

Increasing recent empirical evidence indicates the extensive existence of heavy tails in the inter-event time distributions of various human behaviors. Based on the queuing theory, the Barabasi model and its variations suggest the highest-priority-first protocol to be a potential origin of those heavy tails. However, some human activity patterns, also displaying heavy-tailed temporal statistics, could not be explained by a task-based mechanism. In this paper, different from the mainstream, we propose an interest-based model. Both the simulation and analysis indicate a power-law inter-event time distribution with exponent -1, which is in accordance with some empirical observations in human-initiated systems.