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Identity diversification and homogenization: evidence from frequent estimates of similarity of self-authored, self-descriptive text

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  • Danial Vahabli

    (Stony Brook University)

  • Jason Jeffrey Jones

    (Stony Brook University)

Abstract

For more than a decade, individuals composed and edited self-authored self-descriptions as social media biographies. Did these identities become more diverse over time because of a “rise in individualism” and increasing tolerance or did they become more homogenous through social learning, conformity, and fear of isolation? We analyzed longitudinal and cross-sectional Twitter bio samples with a variety of lexical and semantic methods for the 2012–2022 interval. We show that longitudinally, users diversified on lexical and semantic levels. On a cross-sectional sample—representing the state of the platform at any time point—we again observed a trend of diversification at the lexical level, but a trend of diversification reversed toward re-homogenization on the semantic level. Further, by focusing on local maxima and minima of identity similarity we identified “coordination shocks”—temporally confined intervals where similar users became overactive on the platform and drove short-term deviations from longer-term trends.

Suggested Citation

  • Danial Vahabli & Jason Jeffrey Jones, 2025. "Identity diversification and homogenization: evidence from frequent estimates of similarity of self-authored, self-descriptive text," Journal of Computational Social Science, Springer, vol. 8(2), pages 1-18, May.
    • Handle: RePEc:spr:jcsosc:v:8:y:2025:i:2:d:10.1007_s42001-025-00358-y
    DOI: 10.1007/s42001-025-00358-y
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    References listed on IDEAS

    as
    1. 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.
    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.
    3. Michael Green & Ania Bobrowicz & Chee Siang Ang, 2015. "The lesbian, gay, bisexual and transgender community online: discussions of bullying and self-disclosure in YouTube videos," Behaviour and Information Technology, Taylor & Francis Journals, vol. 34(7), pages 704-712, July.
    4. Jason J Jones & Robert M Bond & Eytan Bakshy & Dean Eckles & James H Fowler, 2017. "Social influence and political mobilization: Further evidence from a randomized experiment in the 2012 U.S. presidential election," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-9, April.
    5. Jones, Jason Jeffrey, 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_v1, Center for Open Science.
    6. Eady, Gregory & Hjorth, Frederik & Dinesen, Peter Thisted, 2023. "Do Violent Protests Affect Expressions of Party Identity? Evidence from the Capitol Insurrection," American Political Science Review, Cambridge University Press, vol. 117(3), pages 1151-1157, August.
    7. Robert M. Bond & Christopher J. Fariss & Jason J. Jones & Adam D. I. Kramer & Cameron Marlow & Jaime E. Settle & James H. Fowler, 2012. "A 61-million-person experiment in social influence and political mobilization," Nature, Nature, vol. 489(7415), pages 295-298, September.
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