Community structure based node scores for network immunization

  • Authors:
  • Tetsuya Yoshida;Yuu Yamada

  • Affiliations:
  • Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan;Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan

  • Venue:
  • PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
  • Year:
  • 2012

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Abstract

We propose community structure based node scores for network immunization. Since epidemics (e.g, virus) are propagated among groups of nodes (communities) in a network, network immunization has often been conducted by removing nodes with large score (e.g., centrality) so that the major part of the network can be protected from the contamination. Since communities are often interwoven through intermediating nodes, we propose to identify such nodes based on the community structure of a network. By regarding the community structure in terms of nodes, we construct a vector representation of each node based on a quality measure of communities for node partitioning. Two types of node score are proposed based on the direction and the norm of the constructed node vectors.