Analytical study of quality-biased competition dynamics for memes in social media

The spreading of news, memes and other pieces of information occurring via online social platforms has a strong and growing impact on our modern societies, with enormous consequences, that may be beneficial but also catastrophic. In this work we consider a recently introduced model for information diffusion in social media taking explicitly into account the competition of a large number of items of diverse quality. We map the meme dynamics onto a one-dimensional diffusion process that we solve analytically, deriving the lifetime and popularity distributions of individual memes. We also present a mean-field type of approach that reproduces the average stationary properties of the dynamics. In this way we understand in detail how the different ingredients of the model (size of users memory, rate of introduction of new memes, intrinsic meme fitness) affect meme spreading at the individual and collective level. This opens the path for the inclusion of additional, more realistic, features, such as heterogeneities in the behavior of individual users. Copyright (C) EPLA, 2018