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Towards understanding how users decide about friendship requests in Online Social Networks Rashtian, Hootan
Abstract
Accepting friend requests from strangers in Facebook-like online social networks is known to be a risky behavior. Still, empirical evidence suggests that Facebook users often accept such requests with high rate. As a first step towards technology support of users in their decisions about friend requests, we investigate why users accept such requests. We conducted two studies of users’ befriending behavior on Facebook. Based on 20 interviews with active Facebook users, we developed a friend request acceptance model that explains how various factors influence user acceptance behavior. To test and refine our model, we also conducted a quantitative study with 397 participants using Amazon Mechanical Turk. We found that four factors significantly impact the receiver’s decision towards requests sent from strangers, namely, knowing the requester’s in real world, having common hobbies or interests, having mutual friends, and the closeness of mutual friends. Based on our findings, we offer design recommendations for improving the usability of the corresponding user interfaces in order to help users make more informed decisions.
Item Metadata
Title |
Towards understanding how users decide about friendship requests in Online Social Networks
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2014
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Description |
Accepting friend requests from strangers in Facebook-like online social networks
is known to be a risky behavior. Still, empirical evidence suggests that Facebook
users often accept such requests with high rate. As a first step towards technology
support of users in their decisions about friend requests, we investigate why users
accept such requests. We conducted two studies of users’ befriending behavior on
Facebook. Based on 20 interviews with active Facebook users, we developed a
friend request acceptance model that explains how various factors influence user
acceptance behavior. To test and refine our model, we also conducted a quantitative
study with 397 participants using Amazon Mechanical Turk. We found that
four factors significantly impact the receiver’s decision towards requests sent from
strangers, namely, knowing the requester’s in real world, having common hobbies
or interests, having mutual friends, and the closeness of mutual friends. Based on
our findings, we offer design recommendations for improving the usability of the
corresponding user interfaces in order to help users make more informed decisions.
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Genre | |
Type | |
Language |
eng
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Date Available |
2014-07-29
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivs 2.5 Canada
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DOI |
10.14288/1.0167341
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2014-09
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivs 2.5 Canada