Smart Broadcasting: Do You Want to be Seen?

Speaker: Manuel Gomez Rodriguez

Abstract: 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 work, 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.

Bio: Manuel Gomez Rodriguez is a tenure-track faculty at Max Planck Institute for Software Systems. Manuel develops machine learning and large-scale data mining methods for the analysis, modeling and control of large real-world networks and processes that take place over them. He is particularly interested in problems arising in the Web and social media and has received several recognitions for his research, including an Outstanding Paper Award at NIPS’13 and a Best Research Paper Honorable Mention at KDD’10. Manuel holds a MS and PhD in Electrical Engineering from Stanford University and a BS in Electrical Engineering from Carlos III University in Madrid (Spain). You can find more about him at http://www.mpi-sws.org/~manuelgr/.

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