Mining Exceptional Social Behaviour

Carolina Centeio Jorge*, Martin Atzmueller, Behzad M. Heravi, Jenny L. Gibson, Cláudio Rebelo de Sá, Rosaldo J.F. Rossetti

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Abstract

    Essentially, our lives are made of social interactions. These can be recorded through personal gadgets as well as sensors adequately attached to people for research purposes. In particular, such sensors may record real time location of people. This location data can then be used to infer interactions, which may be translated into behavioural patterns. In this paper, we focus on the automatic discovery of exceptional social behaviour from spatio-temporal data. For that, we propose a method for Exceptional Behaviour Discovery (EBD). The proposed method combines Subgroup Discovery and Network Science techniques for finding social behaviour that deviates from the norm. In particular, it transforms movement and demographic data into attributed social interaction networks, and returns descriptive subgroups. We applied the proposed method on two real datasets containing location data from children playing in the school playground. Our results indicate that this is a valid approach which is able to obtain meaningful knowledge from the data.

    Original languageEnglish
    Title of host publicationProgress in Artificial Intelligence
    Subtitle of host publication19th EPIA Conference on Artificial Intelligence, EPIA 2019, Proceedings
    EditorsPaulo Moura Oliveira, Paulo Novais, Luís Paulo Reis
    PublisherSpringer
    Pages460-472
    Number of pages13
    VolumePart II
    ISBN (Electronic)978-3-030-30244-3
    ISBN (Print)978-3-030-30243-6
    DOIs
    Publication statusPublished - 1 Jan 2019
    Event19th EPIA Conference on Artificial Intelligence, EPIA 2019 - Vila Real, Portugal
    Duration: 3 Sep 20196 Sep 2019
    Conference number: 19

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer
    Volume11805
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349
    NameLecture notes in Artificial Intelligence
    PublisherSpringer

    Conference

    Conference19th EPIA Conference on Artificial Intelligence, EPIA 2019
    Abbreviated titleEPIA
    CountryPortugal
    CityVila Real
    Period3/09/196/09/19

    Keywords

    • Network science
    • Social interactions
    • Subgroup discovery

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  • Cite this

    Jorge, C. C., Atzmueller, M., Heravi, B. M., Gibson, J. L., de Sá, C. R., & Rossetti, R. J. F. (2019). Mining Exceptional Social Behaviour. In P. Moura Oliveira, P. Novais, & L. P. Reis (Eds.), Progress in Artificial Intelligence: 19th EPIA Conference on Artificial Intelligence, EPIA 2019, Proceedings (Vol. Part II, pp. 460-472). (Lecture Notes in Computer Science; Vol. 11805), (Lecture notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-030-30244-3_38