Networked experiments and modeling for producing collective identity in a group of human subjects using an iterative abduction framework

Vanessa Cedeno-Mieles, Zhihao Hu, Yihui Ren, Xinwei Deng, Abhijin Adiga, Christopher Barrett, Noshir Contractor, Saliya Ekanayake, Joshua M. Epstein, Brian J. Goode, Gizem Korkmaz, Chris J. Kuhlman, Dustin Machi, Michael W. Macy, Madhav V. Marathe, Naren Ramakrishnan, S. S. Ravi, Parang Saraf, Nathan Self

Research output: Contribution to journalArticle

Abstract

Group or collective identity is an individual’s cognitive, moral, and emotional connection with a broader community, category, practice, or institution. There are many different contexts in which collective identity operates, and a host of application domains where collective identity is important. Collective identity is studied across myriad academic disciplines. Consequently, there is interest in understanding the collective identity formation process. In laboratory and other settings, collective identity is fostered through priming a group of human subjects. However, there have been no works in developing agent-based models for simulating collective identity formation processes. Our focus is understanding a game that is designed to produce collective identity within a group. To study this process, we build an online game platform; perform and analyze controlled laboratory experiments involving teams; build, exercise, and evaluate network-based agent-based models; and form and evaluate hypotheses about collective identity. We conduct these steps in multiple abductive iterations of experiments and modeling to improve our understanding of collective identity as this looping process unfolds. Our work serves as an exemplar of using abductive looping in the social sciences. Findings on collective identity include the observation that increased team performance in the game, resulting in increased monetary earnings for all players, did not produce a measured increase in collective identity among them.

Original languageEnglish (US)
Article number11
JournalSocial Network Analysis and Mining
Volume10
Issue number1
DOIs
StatePublished - Dec 1 2020

Keywords

  • Abduction
  • Abductive loop
  • Agent-based models
  • Collective identity
  • Online social experiments

ASJC Scopus subject areas

  • Information Systems
  • Communication
  • Media Technology
  • Human-Computer Interaction
  • Computer Science Applications

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    Cedeno-Mieles, V., Hu, Z., Ren, Y., Deng, X., Adiga, A., Barrett, C., Contractor, N., Ekanayake, S., Epstein, J. M., Goode, B. J., Korkmaz, G., Kuhlman, C. J., Machi, D., Macy, M. W., Marathe, M. V., Ramakrishnan, N., Ravi, S. S., Saraf, P., & Self, N. (2020). Networked experiments and modeling for producing collective identity in a group of human subjects using an iterative abduction framework. Social Network Analysis and Mining, 10(1), [11]. https://doi.org/10.1007/s13278-019-0620-8