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标题: EVA Extraction, Visualization & Analysis of corporate inter-relationships [打印本页]

作者: snachina    时间: 2017-7-18 21:38
标题: EVA Extraction, Visualization & Analysis of corporate inter-relationships
EVA
Extraction, Visualization & Analysis of corporate inter-relationships
Dataset   EVA
Description
EVA.net directed network with 8343 vertices and 6726 arcs.
Download
EVA.net (ZIP, 204K); included also original files names.txt and ownership.txt.
Background
EVA / Denali is a multidisciplinary research project combining information extraction, information visualization, and social network analysis techniques to bring greater transparency to the public disclosure of inter-relationships between corporations. The project is described in the paper [1].
Abstract: We present EVA, a prototype system for extracting, visualizing, and analyzing corporate ownership information as a social network. Using probabilistic information retrieval and extraction techniques, we automatically extract ownership relationships from heterogeneous sources of online text, including corporate annual reports (10-Ks) filed with the U.S. Securities and Exchange Commission (SEC). A browser-based visualization interface allows users to query the relationship database and explore large networks of companies. Applying the system and methodology to the telecommunications and media industries, we construct an ownership network with 6,726 relationships among 8,343 companies. Analysis reveals a highly clustered network, with over 50% of all companies connected to one another in a single component. Furthermore, ownership activity is highly skewed: 90% of companies are involved in no more than one relationship, but the top ten companies are parents for over 24% of all relationships. We are also able to identify the most influential companies in the network using social network analysis metrics such as degree, betweenness, cutpoints, and cliques. We believe this methodology and tool can aid government regulators, policy researchers, and the general public to interpret complex corporate ownership structures, thereby bringing greater transparency to the public disclosure of corporate inter-relationships.
Note that we do not have ownership relationships for all companies, so there will be companies without links.
An arc (X,Y) from company X to company Y exists in the network if in the company X is an owner of company Y.
Copyright 2002 by Denali Project. If you use this dataset in your research, please use the citation to paper [1] as the source of the data.
"Denali" is the Native American name for the tallest peak in North America. It means "the Great One."
If you have any questions, please contact: John Chuang, Mike Gebbie, Gabe Lucas, Kim Norlen.
History

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