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The Geotemporal Demographics of Twitter Usage

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  • Paul A Longley
  • Muhammad Adnan
  • Guy Lansley

Abstract

This paper presents a preliminary empirical evaluation of the strategic importance of infusing Twitter social media data into classifications of small areas, as a way of moving beyond the nighttime residential geographies of conventional geodemographic classifications. We attempt an empirically based critique of the merits and drawbacks of the use of social media data, in which the value of high spatial and temporal granularity of revealed activity patterns is contrasted with the paucity of individual attribute information. We apply new and novel methods to enrich the profiles of Twitter users in order to generalize about activity patterns in London, our case-study city. More insidious problems in the use of social media data arise from the as-yet-unknown sources and operation of bias in their user bases. Our contribution is to begin to identify and assess the biases inherent in social media usage in social research, and use these to evaluate their deployment in research applications.

Suggested Citation

  • Paul A Longley & Muhammad Adnan & Guy Lansley, 2015. "The Geotemporal Demographics of Twitter Usage," Environment and Planning A, , vol. 47(2), pages 465-484, February.
    • Handle: RePEc:sae:envira:v:47:y:2015:i:2:p:465-484
    DOI: 10.1068/a130122p
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    References listed on IDEAS

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    1. Donald L. Foley & Gerald Breese, 1951. "The Standardization of Data Showing Daily Population Movement into Central Business Districts," Land Economics, University of Wisconsin Press, vol. 27(4), pages 348-353.
    2. Pablo Mateos & Paul A Longley & David O'Sullivan, 2011. "Ethnicity and Population Structure in Personal Naming Networks," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-12, September.
    3. Mark Graham & Matthew Zook, 2013. "Augmented Realities and Uneven Geographies: Exploring the Geolinguistic Contours of the Web," Environment and Planning A, , vol. 45(1), pages 77-99, January.
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    Cited by:

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    3. Hasnat, Md Mehedi & Faghih-Imani, Ahmadreza & Eluru, Naveen & Hasan, Samiul, 2019. "Destination choice modeling using location-based social media data," Journal of choice modelling, Elsevier, vol. 31(C), pages 22-34.
    4. Anna Kovacs-Gyori & Alina Ristea & Clemens Havas & Bernd Resch & Pablo Cabrera-Barona, 2018. "#London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter Data," Urban Planning, Cogitatio Press, vol. 3(1), pages 75-99.

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