Nale Lehmann-Willenbrock

Modeling Temporal Interaction Dynamics in Organizational Settings

Most workplace phenomena take place in dynamic social settings and emerge over time, and scholars have repeatedly called for more research into the temporal dynamics of organizational behavior. One reason for this persistent research gap could be that organizational scholars are not aware of the methodological advances that are available today for modeling temporal interactions and detecting behavioral patterns that emerge over time. To facilitate such awareness, this Methods Corner contribution provides a hands-on tutorial for capturing and quantifying temporal behavioral patterns and for leveraging rich interaction data in organizational settings. We provide an overview of different approaches and methodologies for examining temporal interaction patterns, along with detailed information about the type of data that needs to be gathered in order to apply each method as well as the analytical steps (and available software options) involved in each method. Specifically, we discuss and illustrate lag sequential analysis, pattern analysis, statistical discourse analysis, and visualization methods for identifying temporal patterns in interaction data. We also provide key takeaways for integrating these methods more firmly in the field of organizational research and for moving interaction analytical research forward.

Dynamic Affect in Team Meetings: An Interpersonal Construct Embedded in Dynamic Interaction Processes

Dynamic affect in team meetings: An interpersonal construct embedded in dynamic interaction processes Zhike Lei ESMT European School of Management and Technology Nale Lehmann-Willenbrock VU University Amsterdam Abstract Team meetings are affect-laden environments where team members may motivate and energize, or frustrate and agitate each other. The importance of affect in teams generally and in team meetings particularly has led to a growing body of research that focuses on group affect. Existing conceptual and empirical work has contributed to our understanding of the nature of group affect and its implications for critical organizational phenomena, including emotion convergence and divergence, emotional contagion, emotional norms, and leadership. In this chapter, we review and integrate this literature and suggest directions for future research on affective dynamics during team meetings. We first briefly review contemporary research that has used a compositional approach to group affect. We highlight the need for a dynamic approach to group affect and call for more research in this area. We assess what has been learned and discuss suggestions for future theoretical development and methodological approaches for meetings researchers invested in this important interpersonal, dynamic construct.

Estimating verbal expressions of task and social cohesion in meetings by quantifying paralinguistic mimicry

In this paper we propose a novel method of estimating verbal expressions of task and social cohesion by quantifying the dynamic alignment of nonverbal behaviors in speech. As team cohesion has been linked to team effectiveness and productivity, automatically estimating team cohesion can be a useful tool for assessing meeting quality and broader team functioning. In total, more than 20 hours of business meetings (3-8 people) were recorded and annotated for behavioral indicators of group cohesion, distinguishing between social and task cohesion. We hypothesized that behaviors commonly referred to as mimicry can be indicative of verbal expressions of social and task cohesion. Where most prior work targets mimicry of dyads, we investigated the effectiveness of quantifying group-level phenomena. A dynamic approach was adopted in which both the cohesion expressions and the paralinguistic mimicry were quantified on small time windows. By extracting features solely related to the alignment of paralinguistic speech behavior, we found that 2-minute high and low social cohesive regions could be classified with a 0.71 Area under the ROC curve, performing on par with the state-of-the-art where turn-taking features were used. Estimating task cohesion was more challenging, obtaining an accuracy of 0.64 AUC, outperforming the state-of-the-art. Our results suggest that our proposed methodology is successful in quantifying group-level paralinguistic mimicry. As both the state-of-the-art turn-taking features and mimicry features performed worse on estimating task cohesion, we conclude that social cohesion is more openly expressed by nonverbal vocal behavior than task cohesion.

Perceived group cohesion versus actual social structure: A study using social network analysis of egocentric Facebook networks

Research on group cohesion often relies on individual perceptions, which may not reflect the actual social structure of groups. This study draws on social network theory to examine the relationship between observable structural group characteristics and individual perceptions of group cohesion. Leveraging Facebook data, we extracted and partitioned the social networks of 109 participants into groups using a modularity algorithm. We then surveyed perceptions of cohesion, and computed group density and size using social network analysis. Out of six linear mixed effects models specified, a random intercept and fixed slope model with group size as a predictor of perceived group cohesion emerged as best fitting. Whereas group density was not linked to perceived cohesion, size had a small negative effect on perceived cohesion, suggesting that people perceive smaller groups as more cohesive. We discuss the potential of social network analysis, visualization tools, and Facebook data for advancing research on groups.

Group Interaction Frontiers in Technology

Analysis of group interaction and team dynamics is an important topic in a wide variety of fields, owing to the amount of time that individuals typically spend in small groups for both professional and personal purposes, and given how crucial group cohesion and productivity are to the success of businesses and other organizations. This fact is attested by the rapid growth of fields such as People Analytics and Human Resource Analytics, which in turn have grown out of many decades of research in social psychology, organizational behaviour, computing, and network science, amongst other fields. The goal of this workshop is to bring together researchers from diverse fields related to group interaction, team dynamics, people analytics, multi-modal speech and language processing, social psychology, and organizational behaviour.