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Compositional Subgroup Discovery on Attributed Social Interaction Networks

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Discovery Science (DS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11198))

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Abstract

While standard methods for detecting subgroups on plain social networks focus on the network structure, attributed social networks allow compositional analysis, i. e., by exploiting attributive information. Accordingly, this paper applies a compositional perspective for identifying compositional subgroup patterns. In contrast to typical approaches for community detection and graph clustering it focuses on the dyadic structure of social interaction networks. For that, we adapt principles of subgroup discovery – a general data mining technique for the identification of local patterns – to the dyadic network setting. We focus on social interaction networks, where we specifically consider properties of those social interactions, i. e., duration and frequency. In particular, we present novel quality functions for estimating the interestingness of a subgroup and discuss their properties. Furthermore, we demonstrate the efficacy of the approach using two real-world datasets on face-to-face interactions.

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Notes

  1. 1.

    Study participants also gave their informed consent for the use of their data (including their profile) in scientific studies.

  2. 2.

    http://www.sociopatterns.org.

  3. 3.

    http://www.vikamine.org.

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Acknowledgements

This work has been partially supported by the German Research Foundation (DFG) project “MODUS” under grant AT 88/4-1.

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Authors and Affiliations

  1. Department of Cognitive Science and Artificial Intelligence, Tilburg University, Warandelaan 2, 5037 AB, Tilburg, The Netherlands

    Martin Atzmueller

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  1. Martin Atzmueller
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Correspondence to Martin Atzmueller .

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Editors and Affiliations

  1. Goldsmiths University of London, London, UK

    Larisa Soldatova

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Joaquin Vanschoren

  3. University of Cyprus, Nicosia, Cyprus

    George Papadopoulos

  4. Università degli Studi di Bari Aldo Moro, Bari, Italy

    Michelangelo Ceci

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Atzmueller, M. (2018). Compositional Subgroup Discovery on Attributed Social Interaction Networks. In: Soldatova, L., Vanschoren, J., Papadopoulos, G., Ceci, M. (eds) Discovery Science. DS 2018. Lecture Notes in Computer Science(), vol 11198. Springer, Cham. https://doi.org/10.1007/978-3-030-01771-2_17

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  • DOI: https://doi.org/10.1007/978-3-030-01771-2_17

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