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
CountryUnited States
CityDallas
Period8/12/15 → …

Fingerprint Dive into the research topics of 'Zombies Walk Among Us: Cross-platform data mining for event monitoring'. Together they form a unique fingerprint.

Cite this