Citation

BibTex format

@article{Viegas:2019:10.1038/s41598-019-47490-0,
author = {Viegas, EM and Goto, H and Takayasu, H and Takayasu, M and Jensen, HJ},
doi = {10.1038/s41598-019-47490-0},
journal = {Scientific Reports},
title = {Assembling real networks from synthetic and unstructured subsets: the corporate reporting case},
url = {http://dx.doi.org/10.1038/s41598-019-47490-0},
volume = {9},
year = {2019}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - The analysis of interfirm business transaction networks provides invaluable insight into the trading dynamics and economicstructure of countries. However, there is a general scarcity of data available recording real, accurate and extensive informationfor these types of networks. As a result, and in common with other types of network studies - such as protein interactions forinstance - research tends to rely on partial and incomplete datasets, i.e. subsets, with less certain conclusions. Hereh, wemake use of unstructured financial and corporate reporting data in Japan as the base source to construct a financial reportingnetwork, which is then compared and contrasted to the wider real business transaction network. The comparative analysisbetween these two rich datasets - the proxy, partially derived network and the real, complete network at macro as well as localstructural levels - provides an enhanced understanding of the non trivial relationships between partial sampled subsets andfully formed networks. Furthermore, we present an elemental agent based pruning algorithm that reconciles and preserves keystructural differences between these two networks, which may serve as an embryonic generic framework of potentially wideruse to network research, enabling enhanced extrapolation of conclusions from partial data or subsets.
AU - Viegas,EM
AU - Goto,H
AU - Takayasu,H
AU - Takayasu,M
AU - Jensen,HJ
DO - 10.1038/s41598-019-47490-0
PY - 2019///
SN - 2045-2322
TI - Assembling real networks from synthetic and unstructured subsets: the corporate reporting case
T2 - Scientific Reports
UR - http://dx.doi.org/10.1038/s41598-019-47490-0
UR - http://hdl.handle.net/10044/1/71668
VL - 9
ER -