Zombies Walk Among Us: Cross-platform data mining for event monitoring

Emma L Tonkin, Heather Pfeiffer

    Research output: Chapter in Book/Report/Conference proceedingChapter in a book

    Abstract

    Data mining across multiple social websites
    can reveal valuable factual information for both monitoring and
    reconstructing events. Crowdsourcing can be used on these sites
    to monitor ‘flash mob’ group behaviours, loosely or formally
    planned activities, such as ‘zombie walks’. In certain contexts,
    these walks are ‘marketed’ to social site users in order to
    promote charitable or social engagements; in others, analysis
    suggests that participation is a form of political engagement. We
    use multi-platform information extraction to build an atlas of
    geographic and demographic events, which leads us to compelling,
    yet imperfect, understanding of why events are successful and
    regionally relevant factors that encourage people to pick up
    behaviours or participate in movements. More generally, this case
    study confirms to us that that ’big-data’-led analysis of this kind is
    reasonably straightforward and rewarding, as well as providing a
    useful basis for Bayesian reasoning: the use of available evidence
    to evaluate propositions about this type of event.
    Original languageEnglish
    Title of host publicationProceedings of ICDM EEML 2013
    PublisherIEEE Computer Society
    Publication statusPublished - 2013
    EventInternational Workshop on Experimental Economics and Machine Learning , in conjunction with ICDM 2013 - Dallas, United States
    Duration: 8 Dec 2015 → …

    Workshop

    WorkshopInternational Workshop on Experimental Economics and Machine Learning , in conjunction with ICDM 2013
    Country/TerritoryUnited States
    CityDallas
    Period8/12/15 → …

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