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Soft Computing

, Volume 23, Issue 4, pp 1283–1295 | Cite as

A robust method to discover influential users in social networks

  • Qian Ma
  • Jun MaEmail author
Methodologies and Application
  • 127 Downloads

Abstract

Identifying the influential spreaders is an important issue in understanding and controlling the spreading processes in social networks. The key to the influential spreader identification problem is how to evaluate the spreading ability of the nodes. Centralities such as degree, semi-local centrality, betweenness, closeness, k-shell are usually used as evaluation metric. However, we observe that these centralities are sensitive not only to the spreading probability, but also to the network structure. We are not sure which centrality is efficient when we face a new network. In this paper, we propose a robust method named Adjustable multi-Hops Spreading (AHS). In AHS, we refine the influence of a node into direct influence and indirect influence, and then integrate them with a adjustable parameter. The experimental results in both real social networks and artificial networks show that AHS outperforms other centralities in effectiveness, robustness and the distinguish ability.

Keywords

Social networks Influential nodes Spreading Centrality measure 

Notes

Acknowledgements

This work was funded by the Natural Science Foundation of China (61672322, 61672324, 61272240), the Natural Science Foundation of Shandong province (2016ZR E27468, ZR2012FM037) and the Fundamental Research Funds of Shandong University.

Compliance with ethical standards

Conflict of interest

Author Qian Ma declares that she has no conflict of interest. Author Jun Ma declares that he has no conflict of interest.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.School of Computer Science and TechnologyShandong UniversityJinanChina

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