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Residual closeness in networks

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  • Dangalchev, Chavdar

Abstract

A new characteristic (residual closeness) which can measure the network resistance is presented. It evaluates closeness after removal of vertices or links, hence two types are considered—vertices and links residual closeness. This characteristic is more sensitive than the well-known measures of vulnerability—it captures the result of actions even if they are small enough not to disconnect the graph. A definition for closeness is modified so it still can be used for unconnected graphs but the calculations are easier.

Suggested Citation

  • Dangalchev, Chavdar, 2006. "Residual closeness in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 365(2), pages 556-564.
  • Handle: RePEc:eee:phsmap:v:365:y:2006:i:2:p:556-564
    DOI: 10.1016/j.physa.2005.12.020
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    References listed on IDEAS

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    1. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 1999. "Mean-field theory for scale-free random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 272(1), pages 173-187.
    2. Dangalchev, Chavdar, 2004. "Generation models for scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(3), pages 659-671.
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    Cited by:

    1. König, Michael & Liu, Xiaodong & Zenou, Yves, 2014. "R&D Networks: Theory, Empirics and Policy Implications," CEPR Discussion Papers 9872, C.E.P.R. Discussion Papers.
    2. Chen, Duanbing & Lü, Linyuan & Shang, Ming-Sheng & Zhang, Yi-Cheng & Zhou, Tao, 2012. "Identifying influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1777-1787.
    3. Adrian Alter & Ben R. Craig & Peter Raupach, 2015. "Centrality-Based Capital Allocations," International Journal of Central Banking, International Journal of Central Banking, vol. 11(3), pages 329-377, June.
    4. repec:zur:econwp:142 is not listed on IDEAS
    5. repec:spr:scient:v:101:y:2014:i:1:d:10.1007_s11192-014-1358-8 is not listed on IDEAS
    6. Sullivan, J.L. & Novak, D.C. & Aultman-Hall, L. & Scott, D.M., 2010. "Identifying critical road segments and measuring system-wide robustness in transportation networks with isolating links: A link-based capacity-reduction approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 323-336, June.
    7. Ebadi, Ashkan & Schiffauerova, Andrea, 2015. "How to become an important player in scientific collaboration networks?," Journal of Informetrics, Elsevier, vol. 9(4), pages 809-825.
    8. Bíl, Michal & Vodák, Rostislav & Kubeček, Jan & Bílová, Martina & Sedoník, Jiří, 2015. "Evaluating road network damage caused by natural disasters in the Czech Republic between 1997 and 2010," Transportation Research Part A: Policy and Practice, Elsevier, vol. 80(C), pages 90-103.
    9. Hu, Jianqiang & Yu, Jie & Cao, Jinde & Ni, Ming & Yu, Wenjie, 2014. "Topological interactive analysis of power system and its communication module: A complex network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 99-111.
    10. Wang, Xiaojie & Su, Yanyuan & Zhao, Chengli & Yi, Dongyun, 2016. "Effective identification of multiple influential spreaders by DegreePunishment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 238-247.

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