English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Paper

RedQueen: An Online Algorithm for Smart Broadcasting in Social Networks

MPS-Authors
/persons/resource/persons144813

Upadhyay,  Utkarsh
Group M. Gomez Rodriguez, Max Planck Institute for Software Systems, Max Planck Society;

/persons/resource/persons75510

Gomez Rodriguez,  Manuel
Group M. Gomez Rodriguez, Max Planck Institute for Software Systems, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

arXiv:1610.05773.pdf
(Preprint), 977KB

Supplementary Material (public)
There is no public supplementary material available
Citation

Zarezade, A., Upadhyay, U., Rabiee, H., & Gomez Rodriguez, M. (2016). RedQueen: An Online Algorithm for Smart Broadcasting in Social Networks. Retrieved from http://arxiv.org/abs/1610.05773.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002C-F774-F
Abstract
Users in social networks whose posts stay at the top of their followers'{} feeds the longest time are more likely to be noticed. Can we design an online algorithm to help them decide when to post to stay at the top? In this paper, we address this question as a novel optimal control problem for jump stochastic differential equations. For a wide variety of feed dynamics, we show that the optimal broadcasting intensity for any user is surprisingly simple -- it is given by the position of her most recent post on each of her follower's feeds. As a consequence, we are able to develop a simple and highly efficient online algorithm, RedQueen, to sample the optimal times for the user to post. Experiments on both synthetic and real data gathered from Twitter show that our algorithm is able to consistently make a user's posts more visible over time, is robust to volume changes on her followers' feeds, and significantly outperforms the state of the art.