Smart broadcasting: Do you want to be seen?
May 22, 2016 Β· Declared Dead Β· π Knowledge Discovery and Data Mining
"No code URL or promise found in abstract"
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Authors
Mohammad Reza Karimi, Erfan Tavakoli, Mehrdad Farajtabar, Le Song, Manuel Gomez-Rodriguez
arXiv ID
1605.06855
Category
cs.SI: Social & Info Networks
Cross-listed
cs.LG,
stat.ML
Citations
39
Venue
Knowledge Discovery and Data Mining
Last Checked
4 months ago
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 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.
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