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A Dataset for the Study of Identity at Scale: Annual Prevalence of American Twitter Users with specified Token in their Profile Bio - 2015-2020

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  • Jones, Jason J.

    (Stony Brook University)

Abstract

Personally expressed identity is who or what an individual themselves says they are, and it should be studied at scale. At scale means with data on millions of individuals, which is newly available and comes timestamped and geocoded. This work introduces a dataset for the study of identity at scale and describes the method for collecting and aggregating such data. Further, tools and theory for working with the data are presented. A demonstration analysis provides evidence that personal, individual development and changing cultural norms can be observed with these data and methods.

Suggested Citation

  • Jones, Jason J., 2021. "A Dataset for the Study of Identity at Scale: Annual Prevalence of American Twitter Users with specified Token in their Profile Bio - 2015-2020," SocArXiv cm5g7, Center for Open Science.
    • Handle: RePEc:osf:socarx:cm5g7
    DOI: 10.31219/osf.io/cm5g7
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    References listed on IDEAS

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    4. Jun, Seung-Pyo & Yoo, Hyoung Sun & Choi, San, 2018. "Ten years of research change using Google Trends: From the perspective of big data utilizations and applications," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 69-87.
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