Identifying emergent leaders from verbal and nonverbal communications.

International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction

Aran

Mast

et al. 2010

This paper addresses firstly an analysis on how an emergent leader is perceived in newly formed small-groups, and secondly, explore correlations between perception of leadership and automatically extracted nonverbal communicative cues. We hypothesize that the difference in individual nonverbal features between emergent leaders and non-emergent leaders is significant and measurable using speech activity. Our results on a new interaction corpus show that such an approach is promising, identifying the emergent leader with an accuracy of up to 80%.

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identifying emergent leadership in small groups using nonverbal communicative cues

International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction

Aran

Mast

et al. 2010

“…The scenario used in the recordings has been specifically designed to study the possible emergence of leaders. An emergent leader is defined as the person that stands for the group during a face-to-face interaction with no hierarchical roles (predefined) and he/she has the group's sympathy to lead (Stein, 1975). Our corpus also includes a number of annotations on several individual and social concepts collected both from the meeting participants and from multiple external viewers.…”

Section: Introductionmentioning

confidence: 99%

Emergent leaders through looking and speaking: from audio-visual data to multimodal recognition

J Multimodal User Interfaces

Aran

Kumar

et al. 2012

In this paper we present a multimodal analysis of emergent leadership in small groups using audio-visual features and discuss our experience in designing and collecting a data corpus for this purpose. The ELEA AudioVisual Synchronized corpus (ELEA AVS) was collected using a light portable setup and contains recordings of small group meetings. The participants in each group performed the winter survival task and filled in questionnaires related to personality and several social concepts such as leadership and dominance. In addition, the corpus includes annotations on participants' performance in the survival task, and also annotations of social concepts from external viewers. Based on this corpus, we present the feasibility of predicting the emergent leader in small groups using automatically extracted audio and visual features, based on speaking turns and visual attention, and we focus specifically on multimodal features that make use of the looking at participants while speaking and looking at while not speaking measures. Our findings indicate that emergent leadership is related, but not equivalent, to dominance, and while multimodal features bring a moderate degree of effectiveness in inferring the leader, much simpler features extracted from the audio channel are found to give better performance.

“…Leaders stand out in such a way that the group believes he or she, rather than someone else, can make the most of individual differences towards a common objective [27]. The first attempt to identify emergent leaders through their verbal and nonverbal communication was presented in [27], where observers were able to identify the emergent leader by listening to filtered audio or looking at the full transcription of the interaction.…”

Section: Introductionmentioning

confidence: 99%

“…is a group of unacquainted people in which decisions need to be made. An emergent leader is defined as a person that integrates the group towards a common goal having her/his leading force initiative based on the sympathy of the group [27].…”

Section: Introductionmentioning

confidence: 99%

Assessing the impact of language style on emergent leadership perception from ubiquitous audio

Proceedings of the 11th International Conference on Mobile and Ubiquitous Multimedia

Motlíček

Gática-Pérez

2012

Leaders stand out for what they say and how they say it. This work describes the impact of the language style of emergent leaders in small group discussions based on 7 hours of audio from English spoken discussions recorded with a ubiquitous platform. For the language style analysis, word categories are extracted from manual transcriptions of the discussions as well as from automatically detected keywords. The most relevant word categories are then used to predict the emergent leader in each group. Our findings reveal that non-privacy sensitive word categories like amount of words, conjunctions and assent are good predictors of emergent leadership. The emergent leader can be correctly inferred in a fully automatic approach with up to 82% accuracy using categories derived from keywords, and up to 86% using categories derived from full manual transcriptions.