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Information Network Cascading and Network Re-construction with Bounded Rational User Behaviors

机译:信息网络级联和网络重新构建,具有有界的Rational用户行为

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Social media platforms have become increasingly used for both socialization and information diffusion. For example, commercial users can improve their profits by expanding their social media connections to new users. In order to optimize an information provider's network connections, this paper establishes a mathematical model to simulate the behaviours of other users to build connections within the information provider's network. The behaviours include information reposting and following/unfollowing other users. We apply the linear threshold propagation model to determine the reposting actions. In addition, the following or unfollowing actions are modeled by the boundedly rational user equilibrium (BRUE). A three-level optimization model is proposed to maximize total number of connections, which is the goal of the top level. The second level is to simulate user behaviours under BRUE. The third or bottom level is to maximize the other users' utility used in the second level. This paper solves this problem by using exact algorithms for a small-scale synthetic network.
机译:社交媒体平台越来越多地用于社会化和信息扩散。例如,商业用户可以通过将社交媒体连接扩展到新用户来提高其利润。为了优化信息提供商的网络连接,本文建立了一种数学模型,用于模拟其他用户的行为来构建信息提供商网络中的连接。行为包括重新发布和关注/取消关注其他用户的信息。我们应用线性阈值传播模型以确定重新发电操作。此外,以下或不关头的操作是由界限的理性用户平衡(发布)的建模。建议三级优化模型最大化连接总数,这是顶级的目标。第二级是模拟发出的用户行为。第三或底层是最大化第二级中使用的其他用户的实用程序。本文通过使用小规模合成网络的精确算法来解决这个问题。

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