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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 (<jats:italic>k<\/jats:italic>-means algorithm and <jats:inline-formula><jats:alternatives><jats:tex-math>$H\/T$<\/jats:tex-math><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mi>H<\/mml:mi><mml:mo>\/<\/mml:mo><mml:mi>T<\/mml:mi><\/mml:math><\/jats:alternatives><\/jats:inline-formula> 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.<\/jats:p>","DOI":"10.1140\/epjds\/s13688-020-00230-1","type":"journal-article","created":{"date-parts":[[2020,5,7]],"date-time":"2020-05-07T21:02:24Z","timestamp":1588885344000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Comparative analysis of layered structures in empirical investor networks and cellphone communication networks"],"prefix":"10.1140","volume":"9","author":[{"given":"Peng","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun-Chao","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4013-1753","authenticated-orcid":false,"given":"Zhi-Qiang","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8952-8228","authenticated-orcid":false,"given":"Wei-Xing","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7874-7962","authenticated-orcid":false,"given":"Didier","family":"Sornette","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,5,7]]},"reference":[{"key":"230_CR1","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1007\/978-3-319-28361-6_7","volume-title":"Advances in network science","author":"V Arnaboldi","year":"2016","unstructured":"Arnaboldi V, Dunbar RIM, Passarella A, Conti M (2016) Analysis of co-authorship ego networks. 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