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The Role of Information Diffusion in the Evolution of Social Networks

机译:信息传播在社交网络演进中的作用

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Every day millions of users are connected through online social networks, generating a rich trove of data that allows us to study the mechanisms behind human interactions. Triadic closure has been treated as the major mechanism for creating social links: if Alice follows Bob and Bob follows Charlie, Alice will follow Charlie. Here we present an analysis of longitudinal micro-blogging data, revealing a more nuanced view of the strategies employed by users when expanding their social circles. While the network structure affects the spread of information among users, the network is in turn shaped by this communication activity. This suggests a link creation mechanism whereby Alice is more likely to follow Charlie after seeing many messages by Charlie. We characterize users with a set of parameters associated with different link creation strategies, estimated by a Maximum-Likelihood approach. Triadic closure does have a strong effect on link formation, but shortcuts based on traffic are another key factor in interpreting network evolution. However, individual strategies for following other users are highly heterogeneous. Link creation behaviors can be summarized by classifying users in different categories with distinct structural and behavioral characteristics. Users who are popular, active, and influential tend to create traffic-based shortcuts, making the information diffusion process more efficient in the network.
机译:每天都有数百万的用户通过在线社交网络进行连接,生成大量的数据,使我们能够研究人类互动背后的机制。三合会封闭被视为建立社交联系的主要机制:如果爱丽丝跟随鲍勃而鲍勃跟随查理,爱丽丝将跟随查理。在这里,我们对纵向微博数据进行了分析,揭示了用户在扩大社交圈时所采用策略的细微差别。网络结构影响用户之间的信息传播,而网络又受到这种通信活动的影响。这表明了一种链接创建机制,通过该机制,爱丽丝在看到查理的许多消息后更有可能跟随查理。我们使用与最大链接可能性方法估算的与不同链接创建策略相关的一组参数来表征用户。三元组关闭确实对链路形成有很大影响,但是基于流量的快捷方式是解释网络演进的另一个关键因素。但是,跟踪其他用户的个体策略高度不同。可以通过将具有不同结构和行为特征的不同类别的用户分类来总结链接创建行为。受欢迎,活跃和有影响力的用户倾向于创建基于流量的快捷方式,从而使信息传播过程在网络中更加有效。

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