Making Big Data Small: Strategies to Expand Urban and Geographical Research Using Social Media

Ate Poorthuis, Matthew Zook

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

While exciting, Big Data (particularly geotagged social media data) has proven difficult for many urbanists and social science researchers to use. As a partial solution, we propose a strategy that enables the fast extracting of only relevant data from large sets of geosocial data. While contrary to many Big Data approaches—in which analysis is done on the entire dataset—much productive social science work can use smaller datasets—around the same size as census or survey data—within standard methodological frameworks. The approach we outline in this paper—including the example of a fully operating system—offers a solution for urban researchers interested in these types of data but reluctant to personally build data science skills.

Original languageEnglish
Pages (from-to)115-135
Number of pages21
JournalJournal of Urban Technology
Volume24
Issue number4
DOIs
StatePublished - Oct 2 2017

Bibliographical note

Publisher Copyright:
© 2017 The Society of Urban Technology.

Keywords

  • Big data
  • data frameworks
  • data mining
  • social media
  • social science methods
  • twitter

ASJC Scopus subject areas

  • Urban Studies

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