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Empirical analysis of online social networks in the age of Web 2.0

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Author Info

  • Fu, Feng
  • Liu, Lianghuan
  • Wang, Long

Abstract

Today the World Wide Web is undergoing a subtle but profound shift to Web 2.0, to become more of a social web. The use of collaborative technologies such as blogs and social networking site (SNS) leads to instant online community in which people communicate rapidly and conveniently with each other. Moreover, there are growing interest and concern regarding the topological structure of these new online social networks. In this paper, we present empirical analysis of statistical properties of two important Chinese online social networks—a blogging network and an SNS open to college students. They are both emerging in the age of Web 2.0. We demonstrate that both networks possess small-world and scale-free features already observed in real-world and artificial networks. In addition, we investigate the distribution of topological distance. Furthermore, we study the correlations between degree (in/out) and degree (in/out), clustering coefficient and degree, popularity (in terms of number of page views) and in-degree (for the blogging network), respectively. We find that the blogging network shows disassortative mixing pattern, whereas the SNS network is an assortative one. Our research may help us to elucidate the self-organizing structural characteristics of these online social networks embedded in technical forms.

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Bibliographic Info

Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 387 (2008)
Issue (Month): 2 ()
Pages: 675-684

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Handle: RePEc:eee:phsmap:v:387:y:2008:i:2:p:675-684

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Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

Related research

Keywords: Social networks; Blogging networks; Social Networking Site; Topological analysis; (dis)Assortativity;

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Cited by:
  1. Krawczyk, M.J. & Dydejczyk, A. & Kułakowski, K., 2014. "The Simmel effect and babies’ names," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 384-391.
  2. Wang, Junjie & Zhou, Shuigeng & Guan, Jihong, 2011. "Characteristics of real futures trading networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 398-409.
  3. Junseok Hwang & Jorn Altmann & Kibae Kim, 2009. "The Structural Evolution of the Web2.0 Service Network," TEMEP Discussion Papers 200914, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Sep 2009.
  4. Juthasit Rohitratana & Jorn Altmann, 2010. "Agent-Based Simulations of the Software Market under Different Pricing Schemes for Software-as-a-Service and Perpetual Software," TEMEP Discussion Papers 201064, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jul 2010.
  5. Kibae Kim & Jorn Altmann & Junseok Hwang, 2010. "The Impact of the Subgroup Structure on the Evolution of Networks: An Economic Model of Network Evolution," TEMEP Discussion Papers 201056, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Feb 2010.
  6. Kibae Kim & Jorn Altmann, 2013. "Evolution of the Software-as-a-Service Innovation System Through Collective Intelligence," TEMEP Discussion Papers 2013108, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Dec 2013.
  7. Junjie Wang & Shuigeng Zhou & Jihong Guan, 2010. "Characteristics of Real Futures Trading Networks," Papers 1004.4402, arXiv.org, revised Feb 2011.
  8. Kibae Kim & Jorn Altmann, 2011. "A Complex Network Analysis of the Weighted Graph of the Web2.0 Service Network," TEMEP Discussion Papers 201178, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jul 2011.

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