The Impact of the Subgroup Structure on the Evolution of Networks: An Economic Model of Network Evolution
AbstractOne of the most important properties of self-organized networks is their scale-free property. Prior research proved empirically and theoretically that scale-free networks emerge under the preferential attachment rule. However, a few empirical studies also show that empirical networks diverge from the structure of scale-free networks. Empirical networks exhibit a lower exponent of the power law distribution than constructed scale-free networks. Our research aims at establishing a simple evolutionary network model that explains this difference. The results of our model suggest that there are two reasons for this discrepancy. First, as already known, additional links between existing nodes distort the scale-free feature. Second, boundaries between subgroups (groups of network nodes) distort the degree distribution. In general, we believe that our evolutionary model may be applicable not only to describe the structural evolution of networks but also to make network design recommendations in a variety of areas such as WWW-hyperlink networks, business collaboration networks, Peer-To-Peer Networks, and Web2.0 service networks.
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Bibliographic InfoPaper provided by Seoul National University; Technology Management, Economics, and Policy Program (TEMEP) in its series TEMEP Discussion Papers with number 201056.
Length: 24 pages
Date of creation: Feb 2010
Date of revision: Feb 2010
Publication status: Published in NetSciCom2010, IEEE International Workshop on Network Science for Communication Networks, in conjunction with IEEE Infocom 2010, San Diego, USA, March 2010
Social network analysis; scale-free networks; self-organization; evolutionary model; network design; network science; network modeling.;
Find related papers by JEL classification:
- C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
- D02 - Microeconomics - - General - - - Institutions: Design, Formation, and Operations
- D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
- L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
- L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
- L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
- M15 - Business Administration and Business Economics; Marketing; Accounting - - Business Administration - - - IT Management
- M21 - Business Administration and Business Economics; Marketing; Accounting - - Business Economics - - - Business Economics
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-05-22 (All new papers)
- NEP-EVO-2010-05-22 (Evolutionary Economics)
- NEP-NET-2010-05-22 (Network Economics)
- NEP-SOC-2010-05-22 (Social Norms & Social Capital)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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- Kibae Kim & Jorn Altmann & Junseok Hwang, 2010. "An Analysis of the Openness of the Web2.0 Service Network Based on Two Sets of Indices for Measuring the Impact of Service Ownership," TEMEP Discussion Papers 201067, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Oct 2010.
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