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An Estimation Framework of Node Contribution Based on Diffusion Information

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Web and Big Data (APWeb-WAIM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10987))

Abstract

As a key problem in social network studies, identifying important nodes is useful for spreading prediction and restraint. Nowadays, many researches focus on identifying important nodes based on network structure, which is completely necessary. However, the role of a node in diffusion is simultaneously determined by network structure and diffusion characteristics. In this paper, we aim to find the contributive nodes that play important roles in influence spreading without network structure information. First, we formulize the concept of node contribution to influence diffusion to describe the importance of nodes in the spreading processes. Then, we propose an estimation framework and give the method to estimate node contribution based on diffusion samples. Accordingly, the Contribution Estimation algorithm is proposed upon the framework. Finally, we implement our algorithm and test the efficiency on two weighted social networks.

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Notes

  1. 1.

    The datasets are public and available at http://snap.stanford.edu/data/index.html.

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Acknowledgement

This paper was supported by the Research Foundation of Educational Department of Yunnan Province (2017ZZX133), Applied Basic Research Project of Yunnan Province (Youth Program) (2015FD037), National Natural Science Foundation of China (61472345) and Research Foundation of Yunnan University (2017YDJQ06).

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Authors and Affiliations

  1. School of Information Science and Engineering, Yunnan University, Kunming, China

    Zhijian Zhang, Kun Yue & Weiyi Liu

  2. College of Science, Kunming University of Science and Technology, Kunming, China

    Zhijian Zhang

  3. Yunnan Police Officer Academy, Kunming, China

    Ling Liu

Authors
  1. Zhijian Zhang
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  2. Ling Liu
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  3. Kun Yue
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  4. Weiyi Liu
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Corresponding author

Correspondence to Kun Yue .

Editor information

Editors and Affiliations

  1. South China University of Technology, Guangzhou, China

    Yi Cai

  2. Nagoya University, Nagoya, Japan

    Yoshiharu Ishikawa

  3. Hong Kong Baptist University, Kowloon Tong, Hong Kong, China

    Jianliang Xu

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Zhang, Z., Liu, L., Yue, K., Liu, W. (2018). An Estimation Framework of Node Contribution Based on Diffusion Information. In: Cai, Y., Ishikawa, Y., Xu, J. (eds) Web and Big Data. APWeb-WAIM 2018. Lecture Notes in Computer Science(), vol 10987. Springer, Cham. https://doi.org/10.1007/978-3-319-96890-2_11

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  • DOI: https://doi.org/10.1007/978-3-319-96890-2_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-96889-6

  • Online ISBN: 978-3-319-96890-2

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