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Correlation Analysis of Node and Edge Centrality Measures in Artificial Complex Networks

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Proceedings of Sixth International Congress on Information and Communication Technology

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 216))

Abstract

The role of an actor in a social network is identified through a set of measures called centrality. Degree centrality, betweenness centrality, closeness centrality, and clustering coefficient are the most frequently used metrics to compute the node centrality. Their computational complexity in some cases makes unfeasible, when not practically impossible, their computations. For this reason, we focused on two alternative measures, WERW-Kpath and Game of Thieves, which are at the same time highly descriptive and computationally affordable. Our experiments show that a strong correlation exists between WERW-Kpath and Game of Thieves and the classical centrality measures. This may suggest the possibility of using them as useful and more economic replacements of the classical centrality measures.

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Notes

  1. 1.

    Available at http://www.emilio.ferrara.name/code/werw-kpath/.

  2. 2.

    Available at http://github.com/dcmocanu/centrality-metrics-complex-networks.

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Author information

Authors and Affiliations

  1. University of Palermo, Palermo, Italy

    Annamaria Ficara

  2. University of Messina, Messina, Italy

    Annamaria Ficara, Giacomo Fiumara & Pasquale De Meo

  3. University of Bozen-Bolzano, Bozen-Bolzano, Italy

    Antonio Liotta

Authors
  1. Annamaria Ficara
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  2. Giacomo Fiumara
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  3. Pasquale De Meo
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  4. Antonio Liotta
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Corresponding author

Correspondence to Annamaria Ficara .

Editor information

Editors and Affiliations

  1. Middlesex University, London, UK

    Xin-She Yang

  2. The University of Reading, Reading, UK

    Simon Sherratt

  3. JIS University, Kolkata, India

    Nilanjan Dey

  4. Global Knowledge Research Foundation, Ahmedabad, India

    Amit Joshi

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Ficara, A., Fiumara, G., De Meo, P., Liotta, A. (2022). Correlation Analysis of Node and Edge Centrality Measures in Artificial Complex Networks. In: Yang, XS., Sherratt, S., Dey, N., Joshi, A. (eds) Proceedings of Sixth International Congress on Information and Communication Technology. Lecture Notes in Networks and Systems, vol 216. Springer, Singapore. https://doi.org/10.1007/978-981-16-1781-2_78

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