Analyzing group performance in small group interaction: Linking personality traits and group performance through the verbal content

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Date

2019

Authors

Umut Avci
Oya Aran

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Institute of Electrical and Electronics Engineers Inc.

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Green Open Access

Yes

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Abstract

In this paper we investigate the link between the personality traits and group performance in terms of the verbal content. We further study the variability in the verbal interaction between different performance groups. Towards this goal we extract topics representing the content of meetings as well as term-frequencies of items that play a critical role in the decision task. We use a dataset where each group performs the winter survival task in which the task is to decide on the ranking of different items with respect to the importance of each item for their survival. In the experiments we contrast the ranking of items with respect to their term frequencies and compare the differences between topics both for distinct personality traits and group performances. Results of the term-frequency based approach show that influential people put correct emphasis on items more than dominant people. The topic-based method reveals that influential people consider the majority of items by providing usage instructions for alternative scenarios and that dominant people focus only on a small subset of items by stressing their significance. High-performance groups assess items in a similar manner to influential and dominant people i.e. a wide range of items are considered and their importance is explained. Low-performance groups on the other hand concentrate on the situation they are in rather than the items and their usages. © 2020 Elsevier B.V. All rights reserved.

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Keywords

Decision Task, Group Interaction, Group Performance, Performance Group, Personality Traits, Term Frequency, Verbal Interaction, Gesture Recognition, Decision task, Group interaction, Group performance, Performance group, Personality traits, Term Frequency, Verbal interaction, Gesture recognition

Fields of Science

0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

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2

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14th IEEE International Conference on Automatic Face and Gesture Recognition FG 2019

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1

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7
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2

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1

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