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Selection of influential spreaders in complex networks using Pareto Shell decomposition

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  • Yeruva, Sujatha
  • Devi, T.
  • Reddy, Y. Samtha

Abstract

The selection of prominent nodes in order to maximize the ability of spreading is very crucial in complex networks. The well known K-Shell method, which comprises nodes located at the core of a network, is better than the degree centrality and betweenness centrality, in capturing the spreading ability for a single origin spreader. As per the multiple origin spreaders, the K-Shell method fails to yield similar results when compared to the degree centrality. Current research proposes a Pareto-Shell Decomposition. It employs Pareto front function. It’s Pareto optimal set comprises non-dominated spreads, with the ratio of high out-degree to in-degree and high in-degree. Pareto-Shell decomposition outperforms the K-Shell and the degree centrality for multiple origin spreaders, with the simulation of epidemic spreading process.

Suggested Citation

  • Yeruva, Sujatha & Devi, T. & Reddy, Y. Samtha, 2016. "Selection of influential spreaders in complex networks using Pareto Shell decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 133-144.
    • Handle: RePEc:eee:phsmap:v:452:y:2016:i:c:p:133-144
    DOI: 10.1016/j.physa.2016.02.053
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    References listed on IDEAS

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    1. Gert Sabidussi, 1966. "The centrality index of a graph," Psychometrika, Springer;The Psychometric Society, vol. 31(4), pages 581-603, December.
    2. Liu, Jian-Guo & Ren, Zhuo-Ming & Guo, Qiang, 2013. "Ranking the spreading influence in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4154-4159.
    3. Jian-Guo Liu & Zhi-Xi Wu & Feng Wang, 2007. "Opinion Spreading And Consensus Formation On Square Lattice," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 18(07), pages 1087-1094.
    4. Pablo M. Gleiser & Leon Danon, 2003. "Community Structure In Jazz," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(04), pages 565-573.
    5. 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.
    6. Fu, Yu-Hsiang & Huang, Chung-Yuan & Sun, Chuen-Tsai, 2015. "Using global diversity and local topology features to identify influential network spreaders," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 344-355.
    7. Bae, Joonhyun & Kim, Sangwook, 2014. "Identifying and ranking influential spreaders in complex networks by neighborhood coreness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 549-559.
    8. Hou, Bonan & Yao, Yiping & Liao, Dongsheng, 2012. "Identifying all-around nodes for spreading dynamics in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(15), pages 4012-4017.
    9. Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 39-43, March.
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    1. Zhao, Jiuhua & Liu, Qipeng & Wang, Lin & Wang, Xiaofan, 2017. "Competitive seeds-selection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 240-248.

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