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Modeling one-mode projection of bipartite networks by tagging vertex information

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  • Qiao, Jian
  • Meng, Ying-Ying
  • Chen, Hsinchun
  • Huang, Hong-Qiao
  • Li, Guo-Ying

Abstract

Traditional one-mode projection models are less informative than their original bipartite networks. Hence, using such models cannot control the projection’s structure freely. We proposed a new method for modeling the one-mode projection of bipartite networks, which thoroughly breaks through the limitations of the available one-mode projecting methods by tagging the vertex information of bipartite networks in their one-mode projections. We designed a one-mode collaboration network model by using the method presented in this paper. The simulation results show that our model matches three real networks very well and outperforms the available collaboration network models significantly, which reflects the idea that our method is ideal for modeling one-mode projection models of bipartite graphs and that our one-mode collaboration network model captures the crucial mechanisms of the three real systems. Our study reveals that size growth, individual aging, random collaboration, preferential collaboration, transitivity collaboration and multi-round collaboration are the crucial mechanisms of collaboration networks, and the lack of some of the crucial mechanisms is the main reason that the other available models do not perform as well as ours.

Suggested Citation

  • Qiao, Jian & Meng, Ying-Ying & Chen, Hsinchun & Huang, Hong-Qiao & Li, Guo-Ying, 2016. "Modeling one-mode projection of bipartite networks by tagging vertex information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 270-279.
    • Handle: RePEc:eee:phsmap:v:457:y:2016:i:c:p:270-279
    DOI: 10.1016/j.physa.2016.03.106
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    1. Zhang, Pei-Pei & Kan Chen, & He, Yue & Zhou, Tao & Su, Bei-Bei & Jin, Yingdi & Chang, Hui & Zhou, Yue-Ping & Sun, Li-Cheng & Wang, Bing-Hong & He, Da-Ren, 2006. "Model and empirical study on some collaboration networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 599-616.
    2. Zhang, Peng & Wang, Jinliang & Li, Xiaojia & Li, Menghui & Di, Zengru & Fan, Ying, 2008. "Clustering coefficient and community structure of bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6869-6875.
    3. Cesar A. Hidalgo & Ricardo Hausmann, 2009. "The Building Blocks of Economic Complexity," Papers 0909.3890, arXiv.org.
    4. Zhang, Chu-Xu & Zhang, Zi-Ke & Liu, Chuang, 2013. "An evolving model of online bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 6100-6106.
    5. Serguei Saavedra & Felix Reed-Tsochas & Brian Uzzi, 2009. "A simple model of bipartite cooperation for ecological and organizational networks," Nature, Nature, vol. 457(7228), pages 463-466, January.
    6. H. Jeong & B. Tombor & R. Albert & Z. N. Oltvai & A.-L. Barabási, 2000. "The large-scale organization of metabolic networks," Nature, Nature, vol. 407(6804), pages 651-654, October.
    7. Jian-Wei Wang & Li-Li Rong & Qiu-Hong Deng & Ji-Yong Zhang, 2010. "Evolving hypernetwork model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 77(4), pages 493-498, October.
    8. Barabási, A.L & Jeong, H & Néda, Z & Ravasz, E & Schubert, A & Vicsek, T, 2002. "Evolution of the social network of scientific collaborations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 311(3), pages 590-614.
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    1. Hernández, Juan M. & González-Martel, Christian, 2017. "An evolving model for the lodging-service network in a tourism destination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 296-307.

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