文献类型：期刊文献

英文题名：Comparative analysis of layered structures in empirical investor networks and cellphone communication networks

作者：Wang, Peng[1];Ma, Jun-Chao[1];Jiang, Zhi-Qiang[1];Zhou, Wei-Xing[1];Sornette, Didier[2,3]

机构：[1]East China Univ Sci & Technol, Sch Business, Shanghai, Peoples R China;[2]Swiss Fed Inst Technol, Dept Management Technol & Econ, Zurich, Switzerland;[3]Univ Geneva, Swiss Finance Inst, Geneva, Switzerland

年份：2020

卷号：9

期号：1

外文期刊名：EPJ DATA SCIENCE

收录：;EI(收录号：20201908636343);WOS:【SSCI(收录号:WOS:000531010900001)，SCI-EXPANDED(收录号:WOS:000531010900001)】；

基金：This work was partially supported by the National Natural Science Foundation of China (U1811462, 91746108), the Shanghai Philosophy and Social Science Fund Project (2017BJB006), the Program of Shanghai Young Top-notch Talent (2018), the Shanghai Outstanding Academic Leaders Plan, and the Fundamental Research Funds for the Central Universities.

语种：英文

外文关键词：Empirical investor networks; Cellphone communication networks; Layered structure; Cluster analysis

摘要：Empirical investor networks (EIN) proposed by Ozsoylev et al. are assumed to capture the information spreading path among investors. Here, we perform a comparative analysis between the EIN and the cellphone communication networks (CN) to test whether EIN is an information exchanging network from the perspective of the layer structures of ego networks. We employ two clustering algorithms (k-means algorithm and H/T break algorithm) to detect the layer structures for each node in both networks. We find that the nodes in both networks can be clustered into two groups, that one has a layer structure similar to the theoretical Dunbar Circle that alters in ego networks exhibit a four-layer hierarchical structure with the cumulative number of 5, 15, 50 and 150 from the inner layer to the outer layer, and the other one has an additional inner layer with about 2 alters compared with the Dunbar Circle. We also find that the scale ratios, which are estimated based on the unique parameters in the theoretical model of layer structures, conform to a log-normal distribution for both networks. Our results not only deepen our understanding on the topological structures of EIN, but also provide empirical evidence of the channels of information diffusion among investors.