We develop a method to assess the three indicators of transactive memory systems (TMS)—specialization, credibility, and coordination—through computer-aided text analysis. First, human coders assessed group transcripts for phrases representative of these indicators. From those phrases, we identified words that occurred frequently to develop a dictionary of TMS indicators. In total, we analyzed 262 groups composed of 1,091 individuals. Both the human-coded and dictionary-based assessments of TMS indicators are significantly related to a popular survey-based assessment of TMS. Our approach could be used to advance understanding of TMS by analyzing it in contexts where administering surveys is not feasible.

More from our Archive

• DOI: 10.1002/job.2728 2023

  Job embeddedness and voluntary turnover in the face of job insecurity

  Vesa Peltokorpi, David G. Allen

• DOI: 10.1002/job.2727 2023

  Sick and working: Current challenges and emerging directions for future presenteeism research

  Charmi Patel, Michal Biron, Sir Cary Cooper, Pawan S. Budhwar

• DOI: 10.1002/mar.21863 2023

  Use of metaverse in socializing: Application of the big five personality traits framework

  Sowmya G, Debarun Chakraborty, Aruna Polisetty, Sangeeta Khorana, Dimitrios Buhalis

• DOI: 10.1002/smi.3271 2023

  Assessing the physiological basis for resilience in military personnel

  James P. McClung, Meaghan E. Beckner, Emily K. Farina

• DOI: 10.1111/ijsa.12440 2023

  Does it fit? The relationships between personality, decision autonomy fit, work engagement, and emotional exhaustion in self‐managing organizations

  Maria Doblinger, Janina Class

• DOI: 10.1177/10596011231184685 2023

  How Workplace Gossip Shapes Interpersonal Relationships: A Qualitative Study from the Gossip Recipient’s Perspective

  James Greenslade-Yeats, Helena Cooper-Thomas, Rachel Morrison, Patricia D. Corner

• DOI: 10.1002/mar.21871 2023

  Perception of avatars nonverbal behaviors in virtual reality

  Elodie Etienne, Anne‐Lise Leclercq, Angélique Remacle, Laurence Dessart, Michaël Schyns

• DOI: 10.1111/peps.12608 2023

  Improving measurement and prediction in personnel selection through the application of machine learning

  Nick Koenig, Scott Tonidandel, Isaac Thompson, Betsy Albritton, Farshad Koohifar, Georgi Yankov, Andrew Speer, Jay H. Hardy, Carter Gibson, Chris Frost, Mengqiao Liu, Denver McNeney, John Capman, Shane Lowery, Matthew Kitching, Anjali Nimbkar, Anthony Boyce, Tianjun Sun, Feng Guo, Hanyi Min, Bo Zhang, Logan Lebanoff, Henry Phillips, Charles Newton

• DOI: 10.1002/mar.21869 2023

  When less is more: Understanding consumers' responses to minimalist appeals

  Wei‐Fen Chen, Jingshi (Joyce) Liu

• DOI: 10.1111/peps.12612 2023

  Affiliation‐based hiring in startups and the origins of organizational diversity

  Rhett Andrew Brymer, Vera Rocha