Title :
A Nonverbal Behavior Approach to Identify Emergent Leaders in Small Groups
Author :
Sanchez-Cortes, Dairazalia ; Aran, Oya ; Mast, Marianne Schmid ; Gatica-Perez, Daniel
Author_Institution :
Idiap Res. Inst., Martigny, Switzerland
fDate :
6/1/2012 12:00:00 AM
Abstract :
Identifying emergent leaders in organizations is a key issue in organizational behavioral research, and a new problem in social computing. This paper presents an analysis on how an emergent leader is perceived in newly formed, small groups, and then tackles the task of automatically inferring emergent leaders, using a variety of communicative nonverbal cues extracted from audio and video channels. The inference task uses rule-based and collective classification approaches with the combination of acoustic and visual features extracted from a new small group corpus specifically collected to analyze the emergent leadership phenomenon. Our results show that the emergent leader is perceived by his/her peers as an active and dominant person; that visual information augments acoustic information; and that adding relational information to the nonverbal cues improves the inference of each participant´s leadership rankings in the group.
Keywords :
behavioural sciences computing; feature extraction; image classification; inference mechanisms; knowledge based systems; organisational aspects; speech processing; acoustic features extraction; audio channels; collective classification approach; communicative nonverbal cues; emergent leader identification; inference task; nonverbal behavior approach; organizational behavioral research; participant leadership rankings; rule-based approach; small groups; social computing; video channels; visual features extraction; Atmospheric measurements; Feature extraction; Lead; Particle measurements; Sensors; Speech; Visualization; Emergent leadership; nonverbal behavior;
Journal_Title :
Multimedia, IEEE Transactions on
DOI :
10.1109/TMM.2011.2181941