"Dyadosyncrasy", Idiosyncrasy and Demographic Factors in Turn-Taking

2025-05-30

AI Summary

This study investigates how demographic factors (gender, age, education) and individual differences influence turn-taking in English conversation, focusing on transition-floor offsets (TFOs). Using the Fisher corpus—a large-scale collection of naturally occurring dialogues—we applied automated TFO measurement and linear mixed-effects modeling. Results reveal minimal demographic effects: only female and older speakers exhibited marginally shorter TFOs; education showed no significant effect. In contrast, “dyadosyncratic” effects—i.e., strong behavioral convergence within specific dyadic pairs—emerged as the strongest predictor of TFO, explaining 1.8 times more variance than idiosyncratic (individual-level) factors. This work introduces and empirically validates the novel construct “dyadosyncrasy,” demonstrating that conversational rhythm is predominantly shaped by dyadic co-regulation rather than individual traits or group-level demographics. The findings establish a new theoretical framework and methodological paradigm for conversation analysis.

Technology Category

• Natural Language Processing: Discourse, Pragmatics & Argument Mining
• Application Domains: Humanities & Computational Social Science
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction

Application Category

• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems
• Security and Privacy: Large-scale security measurements
• Web Mining and Content Analysis: Models for Web evolution

Abstract

Turn-taking in dialogue follows universal constraints but also varies significantly. This study examines how demographic (sex, age, education) and individual factors shape turn-taking using a large dataset of US English conversations (Fisher). We analyze Transition Floor Offset (TFO) and find notable interspeaker variation. Sex and age have small but significant effects female speakers and older individuals exhibit slightly shorter offsets - while education shows no effect. Lighter topics correlate with shorter TFOs. However, individual differences have a greater impact, driven by a strong idiosyncratic and an even stronger"dyadosyncratic"component - speakers in a dyad resemble each other more than they resemble themselves in different dyads. This suggests that the dyadic relationship and joint activity are the strongest determinants of TFO, outweighing demographic influences.

Problem

• Examines how demographic factors affect turn-taking in conversations
• Analyzes Transition Floor Offset (TFO) and interspeaker variation
• Identifies dyadic relationship as strongest determinant of TFO

Innovation

• Analyze Transition Floor Offset (TFO)
• Identify dyadosyncratic component in dyads
• Compare demographic and individual impacts