RedQueen:社交网络中智能广播的在线算法

Ali Zarezade, U. Upadhyay, H. Rabiee, M. Gomez-Rodriguez
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引用次数: 49

摘要

在社交网络上,帖子在关注者信息流顶部停留时间最长的用户更有可能被注意到。我们能不能设计一个在线算法来帮助他们决定什么时候发布帖子以保持排名前列?在本文中,我们把这个问题作为一个新的跃变随机微分方程的最优控制问题来解决。对于各种各样的feed动态,我们表明,任何用户的最佳广播强度都非常简单?它是由她最近的帖子在她的每个追随者的feed中的位置给出的。因此,我们能够开发一种简单而高效的在线算法,RedQueen,以对用户发布的最佳时间进行采样。对从Twitter收集的合成数据和真实数据进行的实验表明,我们的算法能够始终如一地使用户的帖子随着时间的推移变得更加可见,对她的关注者feed的数量变化具有鲁棒性,并且明显优于目前的技术水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RedQueen: An Online Algorithm for Smart Broadcasting in Social Networks
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.
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