ar X iv :1 31 0. 05 05 v1 [ cs .S I] 1 O ct 2 01 3 Modeling Information Diffusion in Online Social Networks with Partial Differential Equations ∗ Haiyan Wang, Feng Wang, Kuai Xu† School of Mathematical and Natural Sciences Arizona State University, Phoenix, AZ 85069-7100, USA Abstract Online social networks such as Twitter and Facebook have gained tremendous popularity for information exchange. The availability of unprecedented amounts of digital data has accel- erated research on information diffusion in online social networks. However, the mechanism of information spreading in online social networks remains elusive due to the complexity of social interactions and rapid change of online social networks. Much of prior work on information diffusion over online social networks has based on empirical and statistical approaches. The majority of dynamical models arising from information diffusion over online social networks involve ordinary differential
