Communication activity in a social network: relation between long-term correlations and inter-event clustering.

Communication activity in a social network: relation between long-term correlations and inter-event clustering.
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DOI:
10.1038/srep00560
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发表时间:
2012
期刊:
影响因子:
4.6
通讯作者:
Makse, Hernan A.
Makse, Hernan A.
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Rybski, Diego;Buldyrev, Sergey V.;Havlin, Shlomo;Liljeros, Fredrik;Makse, Hernan A.

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社交网络中的人际交流主要受非平凡相关性和时间聚类等统计规律的支配。最近,我们发现用户在社交社区中的活动存在长期相关性。在这里,我们将这项工作扩展到研究整个社区的集体行为,目的是了解集群和长期持久性的起源。在个人层面上,我们发现,在活动的相关性是一个副产品的聚类表示在幂律分布的事件间的时间的单个用户,即短时间内的许多事件被分开的长期没有事件。相反,整个社区的活动呈现出长期的相关性,这是系统真正的涌现属性,即它们与事件间时间的分布无关。这一结果表明,集体行为的存在,可能产生于通过嵌入的社会网络的非平凡的通信模式。
Human communication in social networks is dominated by emergent statistical laws such as non-trivial correlations and temporal clustering. Recently, we found long-term correlations in the user's activity in social communities. Here, we extend this work to study the collective behavior of the whole community with the goal of understanding the origin of clustering and long-term persistence. At the individual level, we find that the correlations in activity are a byproduct of the clustering expressed in the power-law distribution of inter-event times of single users, i.e. short periods of many events are separated by long periods of no events. On the contrary, the activity of the whole community presents long-term correlations that are a true emergent property of the system, i.e. they are not related to the distribution of inter-event times. This result suggests the existence of collective behavior, possibly arising from nontrivial communication patterns through the embedding social network.
DOI: 10.1038/srep00454
发表时间: 2012
期刊: Scientific reports
影响因子: 4.6
作者:
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