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EXTRACTION, VISUALIZATION & ANALYSIS OF THE MEDIA & TELECOMMUNICATIONS OWNERSHIP NETWORK |
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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. To view the visualization:
README Company names Table Ownership Table Paper and Presentation 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, Presentation].
M. Gebbie, G. Lucas, K. Norlen and J. Chuang. Improving Transparency:
Extracting, Visualizing, and Analyzing Corporate Relationships from SEC
10-K Documents, 2002. Under review.
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EVA is part of the Denali Project, supported by the Information Technology Research (ITR) Program of the National Science Foundation. |
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