01321nas a2200193   4500000000100000000000100001008004100002653001600043653001400059653002100073653002300094653002000117100001900137700001500156245008000171300001200251490000700263520085700270       2019                            d10acompetition10ainfluence10ainformation load10alimited at-tention10asocial networks1 aDiego Oliveira1 aKevin Chan00aDiffusion of Information in an Online Social Network with Limited Attention  a362-3740 v433 a<p>This article investigates the competition for limited attention in a social network with innovation. We consider the case where each piece of information has a fitness as proxy of its quality. The higher is the quality, the higher are the chances of being transmitted. We measure the relationship between the quality of an idea and its likelihood of becoming prevalent at the system level. We find that both information overload and limited attention contribute to a degradation of the system discriminative power. When trust is incorporated into the model and the agents can decide whether or not to accept a meme, we show that both lifetime and popularity distributions have broad power-law tails indicating that only a few memes spread virally through the population reproducing perfectly the broad distributions obtained from empirical data.</p>