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A nationwide dataset of de-identified activity spaces derived from geotagged social media data

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  • Ate Poorthuis
  • Qingqing Chen
  • Matthew Zook

Abstract

In this article, we present a historical dataset of activity spaces, originally based on publicly posted and geotagged social media sent within the United States from 2012 to 2019. The dataset, which contains approximately 2 million users and 1.2 billion data points, is de-identified and spatially aggregated to enable ethical and broad sharing across the research community. By publishing the dataset, we hope to help researchers to quickly access and filter data to study people’s activity spaces across a range of places. In this article, we first describe the construction and characteristics of this dataset and then highlight certain limitations of the data through an illustrative analysis of potential bias—an important consideration when using data not collected through representative sampling. Our goal is to empower researchers to create novel, insightful research projects of their own design based on this dataset.

Suggested Citation

  • Ate Poorthuis & Qingqing Chen & Matthew Zook, 2024. "A nationwide dataset of de-identified activity spaces derived from geotagged social media data," Environment and Planning B, , vol. 51(9), pages 2264-2275, November.
    • Handle: RePEc:sae:envirb:v:51:y:2024:i:9:p:2264-2275
    DOI: 10.1177/23998083241264051
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    References listed on IDEAS

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    1. Harvey J. Miller, 2010. "The Data Avalanche Is Here. Shouldn’T We Be Digging?," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 181-201, February.
    2. Ate Poorthuis & Matthew Zook, 2017. "Making Big Data Small: Strategies to Expand Urban and Geographical Research Using Social Media," Journal of Urban Technology, Taylor & Francis Journals, vol. 24(4), pages 115-135, October.
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