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

Ate Poorthuis, Qingqing Chen and Matthew Zook

No sgj4f, OSF Preprints from Center for Open Science

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.

Date: 2024-07-16
New Economics Papers: this item is included in nep-geo and nep-pay
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:sgj4f

DOI: 10.31219/osf.io/sgj4f

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