Influence Maximization within Period under Different Advance Publicity

Abstract

As social network platforms are becoming more and more popular, many activities spread event information through these platforms so that the number of participants during the event can reach the maximum. Note that as time goes by, the event information may be forgotten and repeatedly seen by the users. So the participation intention of a user for the event will change between active and inactive. Therefore, we formulate an influence maximization problem concerning the previous publicity and volatility of user behaviors given a specific period, and propose a fluctuation-aware independent-cascade model to simulate the influence diffusion. Upon the diffusion model, we explored the effects of different advance publicities for influence maximization.