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N Heads Are Better Than None

Morris Hopkins; Mauricio Casteneda; Swapneel Kalpesh Sheth; Gail E. Kaiser

Title:
N Heads Are Better Than None
Author(s):
Hopkins, Morris
Casteneda, Mauricio
Sheth, Swapneel Kalpesh
Kaiser, Gail E.
Date:
Type:
Reports
Department(s):
Computer Science
Persistent URL:
Series:
Columbia University Computer Science Technical Reports
Part Number:
CUCS-025-13
Publisher:
Department of Computer Science, Columbia University
Publisher Location:
New York
Abstract:
Social network platforms have transformed how people communicate and share information. However, as these platforms have evolved, the ability for users to control how and with whom information is being shared introduces challenges concerning the configuration and comprehension of privacy settings. To address these concerns, our crowd sourced approach simplifies the understanding of privacy settings by using data collected from 512 users over a 17 month period to generate visualizations that allow users to compare their personal settings to an arbitrary subset of individuals of their choosing. To validate our approach we conducted an online survey with closed and open questions and collected 59 valid responses after which we conducted follow-up interviews with 10 respondents. Our results showed that 70% of respondents found visualizations using crowd sourced data useful for understanding privacy settings, and 80% preferred a crowd sourced tool for configuring their privacy settings over current privacy controls.
Subject(s):
Computer science
Item views
330
Metadata:
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Suggested Citation:
Morris Hopkins, Mauricio Casteneda, Swapneel Kalpesh Sheth, Gail E. Kaiser, , N Heads Are Better Than None, Columbia University Academic Commons, .

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