Automatic Prediction Of Small Group Performance In Information Sharing Tasks

In this paper, we describe a novel approach, based on Markov jump processes, to model small group conversational dynamics and to predict small group performance. More precisely, we estimate conversational events such as turn taking, backchannels, turn-transitions at the micro-level (1 minute windows...

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Main Authors: Dong, Wen, Lepri, Bruno, Pentland, Alex Paul
Other Authors: Massachusetts Institute of Technology. Media Laboratory
Format: Article
Language:en_US
Published: 2017
Online Access:http://hdl.handle.net/1721.1/108324
https://orcid.org/0000-0002-8053-9983
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author Dong, Wen
Lepri, Bruno
Pentland, Alex Paul
author2 Massachusetts Institute of Technology. Media Laboratory
author_facet Massachusetts Institute of Technology. Media Laboratory
Dong, Wen
Lepri, Bruno
Pentland, Alex Paul
author_sort Dong, Wen
collection MIT
description In this paper, we describe a novel approach, based on Markov jump processes, to model small group conversational dynamics and to predict small group performance. More precisely, we estimate conversational events such as turn taking, backchannels, turn-transitions at the micro-level (1 minute windows) and then we bridge the micro-level behavior and the macro-level performance. We tested our approach with a cooperative task, the Information Sharing task, and we verified the relevance of micro-level interaction dynamics in determining a good group performance (e.g. higher speaking turns rate and more balanced participation among group members).
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spelling mit-1721.1/1083242022-09-30T13:24:43Z Automatic Prediction Of Small Group Performance In Information Sharing Tasks Dong, Wen Lepri, Bruno Pentland, Alex Paul Massachusetts Institute of Technology. Media Laboratory Program in Media Arts and Sciences (Massachusetts Institute of Technology) Pentland, Alex Dong, Wen Lepri, Bruno Pentland, Alex Paul In this paper, we describe a novel approach, based on Markov jump processes, to model small group conversational dynamics and to predict small group performance. More precisely, we estimate conversational events such as turn taking, backchannels, turn-transitions at the micro-level (1 minute windows) and then we bridge the micro-level behavior and the macro-level performance. We tested our approach with a cooperative task, the Information Sharing task, and we verified the relevance of micro-level interaction dynamics in determining a good group performance (e.g. higher speaking turns rate and more balanced participation among group members). Marie Curie COFUND - 7 th Framework (PERSI project) European Commission (PERSI Project within the Marie Curie COFUND-FP7) 2017-04-20T20:42:55Z 2017-04-20T20:42:55Z 2012-04 2012-04 Article http://purl.org/eprint/type/ConferencePaper http://hdl.handle.net/1721.1/108324 Dong, Wen, Bruno Lepri, and Alex (Sandy) Pentland. "Automatic Prediction Of Small Group Performance In Information Sharing Tasks." Collective Intelligence Conference (CI2012), 18-20 April 2012, Cambridge, MA. https://orcid.org/0000-0002-8053-9983 en_US https://arxiv.org/abs/1204.3698 Collective Intelligence Conference, 2012 Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/ application/pdf Prof. Pentland via Phoebe Ayres
spellingShingle Dong, Wen
Lepri, Bruno
Pentland, Alex Paul
Automatic Prediction Of Small Group Performance In Information Sharing Tasks
title Automatic Prediction Of Small Group Performance In Information Sharing Tasks
title_full Automatic Prediction Of Small Group Performance In Information Sharing Tasks
title_fullStr Automatic Prediction Of Small Group Performance In Information Sharing Tasks
title_full_unstemmed Automatic Prediction Of Small Group Performance In Information Sharing Tasks
title_short Automatic Prediction Of Small Group Performance In Information Sharing Tasks
title_sort automatic prediction of small group performance in information sharing tasks
url http://hdl.handle.net/1721.1/108324
https://orcid.org/0000-0002-8053-9983
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