Smart broadcasting: Do you want to be seen?
This addresses the challenge for social media users to gain attention by strategically timing posts, though it is incremental as it builds on existing temporal modeling frameworks.
The paper tackles the problem of optimizing post timing for users in online social networks to maximize visibility, using a temporal point process model and convex optimization to achieve a desired visibility level with provable guarantees, and demonstrates consistent improvements over alternatives on Twitter data.
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 broadcasting 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 broadcasting 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.