Modeling the structure of collective intelligence
Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2010.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2010
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| Online Access: | http://hdl.handle.net/1721.1/57898 |
| _version_ | 1826197668195467264 |
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| author | Dong, Wen |
| author2 | Alex (Sandy) Pentland. |
| author_facet | Alex (Sandy) Pentland. Dong, Wen |
| author_sort | Dong, Wen |
| collection | MIT |
| description | Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2010. |
| first_indexed | 2024-09-23T10:51:18Z |
| format | Thesis |
| id | mit-1721.1/57898 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T10:51:18Z |
| publishDate | 2010 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/578982022-05-26T02:19:00Z Modeling the structure of collective intelligence Dong, Wen Alex (Sandy) Pentland. Massachusetts Institute of Technology. Dept. of Architecture. Program in Media Arts and Sciences. Program in Media Arts and Sciences (Massachusetts Institute of Technology) Architecture. Program in Media Arts and Sciences. Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2010. Cataloged from PDF version of thesis. Includes bibliographical references (p. 85-90). The human problem solution process has attracted an increasing amount of interest among educators, managers, computer scientists and others. However, the discussion of the subject has suffered from the lack of stochastic tools to quantitatively capture both the subtler steps of the problem solution process and the diversity of human thinking. In order to stochastically model the human problem solution, this thesis presents an approach referred to as "influence modeling," that attempts to describe how an individual navigates from one random memory chunk to another related memory chunk, and how a group of people randomly remind one another of memory chunks that could be individually uncommon. As an application of influence modeling, this thesis shows how groups play "20-questions" games based on a semantic space, such as ConceptNet (a common-sense database). It also investigates how groups send signals about their behavior, which are collected by embedded devices, how group interaction processes could be automatically monitored with embedded devices, how group performance could be facilitated, and how to map group behavior and performance from the macroscopic level to the microscopic level in experiments in measuring collective intelligence. The influence modeling makes it possible to understand how a group could perform better than an individual. It also allows for the monitoring of the status of the problem solution, and makes it possible to direct group interaction in more fruitful ways. by Wen Dong. Ph.D. 2010-08-31T16:24:57Z 2010-08-31T16:24:57Z 2010 2010 Thesis http://hdl.handle.net/1721.1/57898 656272810 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 90 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Architecture. Program in Media Arts and Sciences. Dong, Wen Modeling the structure of collective intelligence |
| title | Modeling the structure of collective intelligence |
| title_full | Modeling the structure of collective intelligence |
| title_fullStr | Modeling the structure of collective intelligence |
| title_full_unstemmed | Modeling the structure of collective intelligence |
| title_short | Modeling the structure of collective intelligence |
| title_sort | modeling the structure of collective intelligence |
| topic | Architecture. Program in Media Arts and Sciences. |
| url | http://hdl.handle.net/1721.1/57898 |
| work_keys_str_mv | AT dongwen modelingthestructureofcollectiveintelligence |