社会网络分析论坛 social network analysis forum

 找回密码
 立即注册
查看: 2588|回复: 0
打印 上一主题 下一主题

EVA Extraction, Visualization & Analysis of corporate inter-relationships

[复制链接]

683

主题

924

帖子

998万

积分

管理员

Rank: 9Rank: 9Rank: 9

金币
9977499
贡献
448
威望
448
积分
9980072
跳转到指定楼层
楼主
发表于 2017-7-18 21:38:55 | 只看该作者 回帖奖励 |倒序浏览 |阅读模式
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
  • 2002 collection of original data by the EVA group;
  • March 6, 2004: original data transformed into Pajek format EVA.net by V. Batagelj.

References
  • Kim Norlen, Gabriel Lucas, Mike Gebbie, and John Chuang. EVA: Extraction, Visualization and Analysis of the Telecommunications and Media Ownership Network. Proceedings of International Telecommunications Society 14th Biennial Conference, Seoul Korea, August 2002. (paper berkeley / local; slides berkeley / local)

回复

使用道具 举报

QQ|Archiver|手机版|小黑屋|社会网络分析论坛 social network analysis forum ( 88876751 )

GMT+8, 2024-11-23 09:26 , Processed in 0.190842 second(s), 22 queries .

Powered by www.snachina.com X3.3

© 2001-2017 snachina.com.

快速回复 返回顶部 返回列表