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RedQueen: an online algorithm for smart broadcasting in social networks

Zarezade, A ; Sharif University of Technology | 2017

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  1. Type of Document: Article
  2. DOI: 10.1145/3018661.3018684
  3. Publisher: Association for Computing Machinery, Inc , 2017
  4. Abstract:
  5. 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. © 2017 ACM
  6. Keywords:
  7. Smart broadcasting ; Social networks ; Stochastic optimal control ; Temporal point processes ; Twitter ; Broadcasting ; Data mining ; Differential equations ; Information retrieval ; Optimal control systems ; Stochastic control systems ; Stochastic systems ; Websites ; On-line algorithms ; Optimal broadcasting ; Optimal control problem ; Point process ; Stochastic differential equations ; Synthetic and real data ; Social networking (online)
  8. Source: WSDM 2017 - Proceedings of the 10th ACM International Conference on Web Search and Data Mining, 2 February 2017 ; 2017 , Pages 51-60 ; 9781450346757 (ISBN)
  9. URL: https://dl.acm.org/citation.cfm?id=3018684