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Game-Theoretic Models of Information Overload in Social Networks

机译:社交网络中信息超载的博弈模型

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摘要

We study the effect of information overload on user engagement in an asymmetric social network like Twitter. We introduce simple game-theoretic models that capture rate competition between celebrities producing updates in such networks where users non-strategically choose a subset of celebrities to follow based on the utility derived from high quality updates as well as disutility derived from having to wade through too many updates. Our two variants model the two behaviors of users dropping some potential connections (followership model) or leaving the network altogether (engagement model). We show that under a simple formulation of celebrity rate competition, there is no pure strategy Nash equilibrium under the first model. We then identify special cases in both models when pure rate equilibria exist for the celebrities: For the followership model, we show existence of a pure rate equilibrium when there is a global ranking of the celebrities in terms of the quality of their updates to users. This result also generalizes to the case when there is a partial order consistent with all the linear orders of the celebrities based on their qualities to the users. Furthermore, these equilibria can be computed in polynomial time. For the engagement model, pure rate equilibria exist when all users are interested in the same number of celebrities, or when they are interested in at most two. Finally, we also give a finite though inefficient procedure to determine if pure equilibria exist in the general case of the followership model.
机译:我们研究了诸如Twitter之类的非对称社交网络中信息过载对用户参与的影响。我们引入了简单的博弈论模型,该模型捕获了此类网络中产生更新的名人之间的速率竞争,在这种网络中,用户根据高质量更新产生的效用以及由于必须经过而产生的不实用性,非策略性地选择了名人的一个子集许多更新。我们的两种变体对用户丢弃某些潜在连接(伙伴关系模型)或完全离开网络(参与模型)的两种行为进行了建模。我们表明,在名人率竞争的简单表述下,在第一个模型下没有纯粹的策略纳什均衡。然后,当两个名人存在纯比率均衡时,我们在两种模型中都确定了特殊情况:对于追随者模型,当根据对用户的更新质量对名人进行全球排名时,我们表明存在纯比率均衡。该结果还推广到以下情况:根据用户对用户的素质,存在与名人的所有线性顺序一致的部分顺序。此外,这些平衡可以在多项式时间内计算。对于参与度模型,当所有用户都对相同数量的名人感兴趣或最多对两个名人感兴趣时,就存在纯利率均衡。最后,我们还给出了一个有限但效率低下的过程来确定在追随者模型的一般情况下是否存在纯均衡。

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  • 来源
  • 会议地点 Stanford CA(US);Stanford CA(US)
  • 作者单位

    Microsoft Research New England, Cambridge, MA;

    Microsoft Research New England, Cambridge, MA;

    Microsoft Research New England, Cambridge, MA, University of Michigan, Ann Arbor;

    Microsoft Research New England, Cambridge, MA, Carnegie Mellon University;

    Microsoft Research New England, Cambridge, MA, Carnegie Mellon University;

    Microsoft Research New England, Cambridge, MA, MIT Sloan School of Management;

    Microsoft Research New England, Cambridge, MA, Carnegie Mellon University;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计算机网络;
  • 关键词

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