Generalized friendship paradox in complex networks: The case of scientific collaboration
Generalized friendship paradox in complex networks: The case of scientific collaboration
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DOI：
10.1038/srep04603
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发表时间：
2014-04-08
影响因子：
4.6
通讯作者：
Jo, Hang-Hyun
中科院分区：
文献类型：
--
作者：
Eom, Young-Ho;Jo, Hang-Hyun
友谊悖论指出，你的朋友平均比你拥有更多的朋友。这个悖论对于收入或幸福感等其他个体特征是否“成立”？为了解决这个问题，我们将友谊悖论推广到复杂网络中任意节点特征。通过分析物理评论期刊和谷歌学术档案的两个合着网络，我们发现广义友谊悖论（GFP）在个体和网络层面上对于各种特征都成立，包括合著者数量、引用数量和出版物数量。GFP 的起源被证明植根于作为 GFP 的一种富有成效的应用，我们提出了用于识别大规模网络中高特征节点的有效且高效的采样方法，我们对 GFP 的研究可以帮助理解复杂网络中网络结构和节点特征之间的相互作用。
The friendship paradox states that your friends have on average more friends than you have. Does the paradox "hold'' for other individual characteristics like income or happiness? To address this question, we generalize the friendship paradox for arbitrary node characteristics in complex networks. By analyzing two coauthorship networks of Physical Review journals and Google Scholar profiles, we find that the generalized friendship paradox (GFP) holds at the individual and network levels for various characteristics, including the number of coauthors, the number of citations, and the number of publications. The origin of the GFP is shown to be rooted in positive correlations between degree and characteristics. As a fruitful application of the GFP, we suggest effective and efficient sampling methods for identifying high characteristic nodes in large-scale networks. Our study on the GFP can shed lights on understanding the interplay between network structure and node characteristics in complex networks.