Many users in online social networks are constantly trying to gain attention from their followers by broadcasting posts to them. These broadcasters are likely to gain greater attention if their posts can remain visible for a longer period of time among their followers’ most recent feeds. Then when to post? In this paper, we study the problem of smart broad-casting using the framework of temporal point processes, where we model users feeds and posts as discrete events occurring in continuous time. Based on such continuous-time model, then choosing a broadcasting strategy for a user becomes a problem of designing the conditional intensity of her posting events. We derive a novel formula which links this conditional intensity with the “visibility” of the user in her followers’ feeds. Furthermore, by exploiting this formula, we develop an efficient convex optimization framework for the “when-to-post” problem. Our method can find broad-casting strategies that reach a desired “visibility” level with provable guarantees. We experimented with data gathered from Twitter, and show that our framework can consistently make broadcasters’ post more visible than alternatives.

Filed under: Graph Mining and Social Networks