Diffusion approximation of a network model of meme popularity

Models of meme propagation on social networks, in which memes compete for limited user attention, can successfully reproduce the heavy-tailed popularity distributions observed in online settings. While system-wide popularity distributions have been derived analytically, the dynamics of individual meme trajectories have thus far evaded description. To address this, we formulate the diffusion of a given meme as a one-dimensional stochas-tic process, whose fluctuations result from aggregating local network dynamics using classic and generalized central limit theorems, with the latter based on stable distribution theory. Ultimately, our approach decouples competing trajectories of meme popularities, allowing them to be simulated independently, and thus parallelized and expressed in terms of Fokker-Planck equations.