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Capturing passion expressed in text with artificial intelligence (AI): Affective passion waned, and identity centrality was sustained in social ventures

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  • Williamson, Amanda Jasmine
  • Battisti, Martina
  • Pollack, Jeffrey M.

Abstract

Entrepreneurial passion can influence individual well-being and improve firm-level outcomes, yet little is known about how to rapidly detect a change in passion from entrepreneurs’ communication. We draw on advancements in both the passion literature and artificial intelligence (AI) methods, to capture entrepreneurial passion expressed for founding a venture at different points in time. Specifically, we developed an AI algorithm to recognize identity-based passion (identity centrality) from training data, comprised of 8 h of transcribed interviews with entrepreneurs (achieving 84% accuracy), and detect affective passion (intense positive feelings) with sentiment analysis. Application of these two novel measurement approaches, to longitudinal interview text with early-stage entrepreneurs (N = 11, two time periods) in a six-month social venture accelerator, indicate that intense positive feelings decline while identity centrality varies. We conclude by outlining opportunities for future research.

Suggested Citation

  • Williamson, Amanda Jasmine & Battisti, Martina & Pollack, Jeffrey M., 2022. "Capturing passion expressed in text with artificial intelligence (AI): Affective passion waned, and identity centrality was sustained in social ventures," Journal of Business Venturing Insights, Elsevier, vol. 17(C).
    • Handle: RePEc:eee:jobuve:v:17:y:2022:i:c:s2352673421000731
    DOI: 10.1016/j.jbvi.2021.e00295
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    References listed on IDEAS

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