Exploring Meeting Dynamics Indicators using Keyword Co-occurrence Networks

Abstract

One promising approach to improving meeting efficiency and productivity is to support meetings through in-meeting interventions based on real-time monitoring of meeting dynamics. This study investigates the validity of meeting dynamics indicators computed using Keyword Co-occurrence Networks and principal component analysis, which were proposed in our previous study. More specifically, this study examines the relationship between these indicators and meeting quality, as well as their context dependence, to clarify their applicability to monitoring and supporting meeting states. Verbal data collected from real-world corporate meetings and controlled meeting experiments were analyzed. Meeting dynamics indicators were computed from the spoken content of the meetings, and their relationships with perceived meeting processes and objective meeting outcomes were assessed using correlation analyses and analyses of variance. These analyses were used to evaluate the validity and context dependence of the indicators. The results indicate that the indicators are more strongly associated with perceived meeting performance than with objective meeting outcomes, and that their interpretation and effectiveness depend strongly on meeting type, including its structure. Overall, these findings suggest that meeting dynamics indicators can function as metacognitive cues that help participants reflect on their current meeting state in intervention settings, and that they may serve as practical indicators to support monitoring of meeting states and iterative improvement cycles for meeting processes.

Keywords: Meeting Evaluation, Meeting Dynamics Indicator, Keyword Co-occurrence Network, Principal Component Analysis, Validity, Context Dependence

DOI: 10.54941/ahfe1007618