Delayed information cascades in Flickr : measurement, analysis, and modeling.

Abstract

Online social networks exhibit small-world network characteristics, implying that information can spread in the network quickly and widely. This ability to spread information rapidly has led to high expectations for word-of-mouth and viral campaigns in online social networks. However, a recent study of the Flickr social network has shown that popular photos do not spread as quickly as one might expect, but show a steady linear growth of popularity over several years. In this paper, we investigate possible reasons for this delay in word-of-mouth propagation by studying the behavior of Flickr users. We identify two factors of a social network that can alter how information spreads: the burstiness of user login times and content aging. We study the impact of these factors using an epidemiological model that was adapted to allow us to investigate the speed of propagation in word-ofmouth propagation. Our simulation shows that the two factors can explain the patterns observed on the real data and help us to understand how these factors affect a small-world network’s ability to spread information quickly and widely.