2026-09-19T13:10:19Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/854432026-06-06T00:48:48Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Constantinos Daskalakis.
Long, Sunny (Sunny X.)
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2014-03-06T15:42:23Z
2014-03-06T15:42:23Z
2013
2013
http://hdl.handle.net/1721.1/85443
870684800
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 77-79).
In my research, I designed and implemented an online game accessable to a large diverse audience via the Facebook social network to test out game theoretic results and study social interactions. In this game, we designed scenarios that mirrored classic game theory situations, most prominantly the Iterated Prisoner's Dilemma game. The game allows for Facebook users to play each other in the Prisoner's Dilemma game while competing for a common goal. We then gather data on strategies employed by players and compare them to classic game theoretic results and try to explain similarities and differences. We also look at social factors that were prominant in decision-making for players. Analysis includes disecting which factors (e.g. gender, age, etc.) affect players' decisions and understanding winning strategies. We discovered that under the social setting of the experiment, factors that came into play for users' decision-making included gender as well as potential payoffs. On the other hand, game play history and whether or not two people were friends were not significant in decision-making. Despite a high overall cooperation rate (over 70%), the top players predominantly betrayed their opponents while never playing the same opponent too many times. The game is implemented in Ruby on Rails while all data analysis is done via Python scripts.
by Sunny Long.
M.Eng.
79 pages
eng
Massachusetts Institute of Technology
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
Electrical Engineering and Computer Science.
Testing theoretical game theory results on a large scale : prisoner's dilemma on Facebook
Thesis
application/pdf
false
Publication
unknown
unknown
<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="11faf732-aeb5-4abf-bb63-9cc41ecba58c">
<Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type>
<Language>eng</Language>
<Title>Testing theoretical game theory results on a large scale : prisoner's dilemma on Facebook</Title>
<PublishedIn>
<Publication>
</Publication>
</PublishedIn>
<PublicationDate>2013</PublicationDate>
<Authors>
<Author>
<DisplayName>Long, Sunny (Sunny X.)</DisplayName>
<Affiliation>
<OrgUnit>
</OrgUnit>
</Affiliation>
</Author>
</Authors>
<Editors>
</Editors>
<Publishers>
<Publisher>
<DisplayName>Massachusetts Institute of Technology</DisplayName>
<OrgUnit />
</Publisher>
</Publishers>
<License>http://dspace.mit.edu/handle/1721.1/7582</License>
<Keyword>Electrical Engineering and Computer Science.</Keyword>
<Abstract>In my research, I designed and implemented an online game accessable to a large diverse audience via the Facebook social network to test out game theoretic results and study social interactions. In this game, we designed scenarios that mirrored classic game theory situations, most prominantly the Iterated Prisoner's Dilemma game. The game allows for Facebook users to play each other in the Prisoner's Dilemma game while competing for a common goal. We then gather data on strategies employed by players and compare them to classic game theoretic results and try to explain similarities and differences. We also look at social factors that were prominant in decision-making for players. Analysis includes disecting which factors (e.g. gender, age, etc.) affect players' decisions and understanding winning strategies. We discovered that under the social setting of the experiment, factors that came into play for users' decision-making included gender as well as potential payoffs. On the other hand, game play history and whether or not two people were friends were not significant in decision-making. Despite a high overall cooperation rate (over 70%), the top players predominantly betrayed their opponents while never playing the same opponent too many times. The game is implemented in Ruby on Rails while all data analysis is done via Python scripts.</Abstract>
<Access xmlns="http://purl.org/coar/access_right"
>
</Access>
</Publication>