A dataset for the study of identity at scale: Annual Prevalence of American Twitter Users with specified Token in their Profile Bio 2015-2020.

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...

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Auteur principal: Jason Jeffrey Jones
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Langue:EN
Publié: Public Library of Science (PLoS) 2021
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Accès en ligne:https://doaj.org/article/7eaad403fca4401e83e4b59cb55cafa6
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spelling oai:doaj.org-article:7eaad403fca4401e83e4b59cb55cafa62021-12-02T20:12:41ZA dataset for the study of identity at scale: Annual Prevalence of American Twitter Users with specified Token in their Profile Bio 2015-2020.1932-620310.1371/journal.pone.0260185https://doaj.org/article/7eaad403fca4401e83e4b59cb55cafa62021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0260185https://doaj.org/toc/1932-6203Personally 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.Jason Jeffrey JonesPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11, p e0260185 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Jason Jeffrey Jones
A dataset for the study of identity at scale: Annual Prevalence of American Twitter Users with specified Token in their Profile Bio 2015-2020.
description 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.
format article
author Jason Jeffrey Jones
author_facet Jason Jeffrey Jones
author_sort Jason Jeffrey Jones
title A dataset for the study of identity at scale: Annual Prevalence of American Twitter Users with specified Token in their Profile Bio 2015-2020.
title_short A dataset for the study of identity at scale: Annual Prevalence of American Twitter Users with specified Token in their Profile Bio 2015-2020.
title_full A dataset for the study of identity at scale: Annual Prevalence of American Twitter Users with specified Token in their Profile Bio 2015-2020.
title_fullStr A dataset for the study of identity at scale: Annual Prevalence of American Twitter Users with specified Token in their Profile Bio 2015-2020.
title_full_unstemmed A dataset for the study of identity at scale: Annual Prevalence of American Twitter Users with specified Token in their Profile Bio 2015-2020.
title_sort dataset for the study of identity at scale: annual prevalence of american twitter users with specified token in their profile bio 2015-2020.
publisher Public Library of Science (PLoS)
publishDate 2021
url https://doaj.org/article/7eaad403fca4401e83e4b59cb55cafa6
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