Application of social media data to high-resolution mapping of a special event population

Kelly M. Sims, Eric M. Weber, Budhendra L. Bhaduri, Gautam S. Thakur, David R. Resseguie

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

8 Scopus citations

Abstract

Society’s increasing participation in social media provides access to new sources of near-real-time data that reflect our activities in space and in time. The ability for users to capture and express their geolocations through their phones’ global positioning system (GPS), or through a particular location’s hashtag or Facebook page, provides an opportunity for modeling spatiotemporal population dynamics. One illustrative application is the modeling of dynamic populations associated with special events such as sporting events. To demonstrate, Twitter posts and Facebook check-ins were collected across a 24 h period for several football game days at the University of Tennessee, Knoxville, during the 2013 season.Population distributions for game hours and nongame hours of a typical game day were modeled at a high spatial resolution using the spatiotemporal distributions of the social media data.

Original languageEnglish
Title of host publicationAdvances in Geocomputation - Geocomputation 2015—The 13th International Conference
EditorsDaniel A. Griffith, Yongwan Chun, Denis J. Dean
PublisherSpringer Heidelberg
Pages67-74
Number of pages8
ISBN (Print)9783319227856
DOIs
StatePublished - 2017
Event13th International Conference on Advances in Geocomputation, Geocomputation 2015 - Dallas, United States
Duration: May 20 2015May 23 2015

Publication series

NameAdvances in Geographic Information Science
ISSN (Print)1867-2434
ISSN (Electronic)1867-2442

Conference

Conference13th International Conference on Advances in Geocomputation, Geocomputation 2015
Country/TerritoryUnited States
CityDallas
Period05/20/1505/23/15

Funding

This manuscript has been authored by employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy. Accordingly, the United States Government retains, and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

Keywords

  • Population
  • Population modeling
  • Social media

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