Information Sharing for Collective Sensemaking
Information Sharing for Collective Sensemaking
Group decision tasks that require pooling of information to reach the best decision have been studied across a variety of disciplines over the past thirty years. The crucial question of what makes these tasks so difficult, however remains unanswered. Various hypotheses include inefficiency in sharing information leading to decisions based on incomplete information or cognitive inefficiencies in processing and storing information arriving in a piecemeal fashion. The present study attacks this problem from two directions. Human experiments are used to compare decisions between groups manipulated to receive and share information in raw and aggregated forms and mixed groups comprised of humans and software agents. To shed light on cognitive limitations that may affect performance, an ACT-R cognitive model of group members was constructed and its results compared to human data.
Tang, Yuqing
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Lebiere, Christian
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Sycara, Katia
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Morrison, Don
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Lewis, Michael
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Smart, Paul
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5 January 2016
Tang, Yuqing
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Lebiere, Christian
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Sycara, Katia
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Morrison, Don
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Lewis, Michael
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Smart, Paul
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Tang, Yuqing, Lebiere, Christian, Sycara, Katia, Morrison, Don, Lewis, Michael and Smart, Paul
(2016)
Information Sharing for Collective Sensemaking.
Hawaii International Conference on System Sciences, Kauai, Hawaii, United States.
05 - 08 Jan 2016.
9 pp
.
(doi:10.1109/HICSS.2016.53).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Group decision tasks that require pooling of information to reach the best decision have been studied across a variety of disciplines over the past thirty years. The crucial question of what makes these tasks so difficult, however remains unanswered. Various hypotheses include inefficiency in sharing information leading to decisions based on incomplete information or cognitive inefficiencies in processing and storing information arriving in a piecemeal fashion. The present study attacks this problem from two directions. Human experiments are used to compare decisions between groups manipulated to receive and share information in raw and aggregated forms and mixed groups comprised of humans and software agents. To shed light on cognitive limitations that may affect performance, an ACT-R cognitive model of group members was constructed and its results compared to human data.
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HICSS_2016_FINAL.pdf
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Published date: 5 January 2016
Venue - Dates:
Hawaii International Conference on System Sciences, Kauai, Hawaii, United States, 2016-01-05 - 2016-01-08
Organisations:
Web & Internet Science
Identifiers
Local EPrints ID: 382576
URI: http://eprints.soton.ac.uk/id/eprint/382576
PURE UUID: 790268c0-bcef-4913-9287-d88353b373d7
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Date deposited: 06 Oct 2015 17:48
Last modified: 15 Mar 2024 03:15
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Contributors
Author:
Yuqing Tang
Author:
Christian Lebiere
Author:
Katia Sycara
Author:
Don Morrison
Author:
Michael Lewis
Author:
Paul Smart
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