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Using GPS Geo-tagged Social Media Data and Geodemographics to Investigate Social Differences: A Twitter Pilot Study

Author

Listed:
  • Paul Chappell

    (Independent Scholar)

  • Mike Tse

    (University of York, UK)

  • Minhao Zhang

    (University of York, UK)

  • Susan Moore

    (University of York, UK)

Abstract

This article outlines a new method for investigating social position through geo-tagged Twitter data, specifically through the application of the geodemographic classification system Mosaic. The method involves the identification of a given tweeter’s likely location of residence from the ‘geo-tag’ attached to their tweet. Using this high-resolution geographic information, each individual tweet is then attributed a geodemographic classification. This article shows that the specific application of geodemographics for discerning between different types of tweeters is problematic in some ways, but that the general process of classifying tweeters according to their position in geographical space is viable and represents a powerful new method for discerning the social position of tweeters. Further research is required in this area, as there is great potential in employing the mobile global positioning system data appended to digital by-product data to explore the intersections between geographical space and social position.

Suggested Citation

  • Paul Chappell & Mike Tse & Minhao Zhang & Susan Moore, 2017. "Using GPS Geo-tagged Social Media Data and Geodemographics to Investigate Social Differences: A Twitter Pilot Study," Sociological Research Online, , vol. 22(3), pages 38-56, September.
    • Handle: RePEc:sae:socres:v:22:y:2017:i:3:p:38-56
    DOI: 10.1177/1360780417724065
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    References listed on IDEAS

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