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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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  • Jason Jeffrey Jones

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.

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  • Jason Jeffrey Jones, 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," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-17, November.
    • Handle: RePEc:plo:pone00:0260185
    DOI: 10.1371/journal.pone.0260185
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    References listed on IDEAS

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    1. Robert Griffo & Edward Lemay & Amanda H. Moreno, 2021. "Who Am I? Let Me Think: Assessing the Considered Self-Concept," SAGE Open, , vol. 11(1), pages 21582440211, March.
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    2. 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.

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