DocumentCode
1976614
Title
Blind Spots: Unveiling users´ true willingness in online social networks
Author
Di Wang ; Xinxin Liu ; Xiaolin Li
Author_Institution
Scalable Software Syst. Lab., Univ. of Florida, Gainesville, FL, USA
fYear
2012
fDate
3-7 Dec. 2012
Firstpage
2066
Lastpage
2071
Abstract
Although online social networks reflect real world social relationships, in many cases, online data is too scarce or implicit to reveal a user´s true willingness. This causes the Blind Spot problem in socially-rendered willingness inference systems. Blind spots are the undervalued online contacts in willingness inference because of insufficient explicit evidences. To the best of our knowledge, this is the first time to introduce and address the blind spot problem. In this paper, we propose a scheme to detect blind spots, by contradicting explicit evidences and implicit inferences. The proposed scheme uses interaction history as the explicit evidence, and social circles for implicit inference. Real world experiments and surveys demonstrate that our scheme can detect blind spots.
Keywords
inference mechanisms; social networking (online); user interfaces; blind spot problem; explicit evidence; implicit inference; online contact; online social network; social relationship; socially-rendered willingness inference system; user true willingness;
fLanguage
English
Publisher
ieee
Conference_Titel
Global Communications Conference (GLOBECOM), 2012 IEEE
Conference_Location
Anaheim, CA
ISSN
1930-529X
Print_ISBN
978-1-4673-0920-2
Electronic_ISBN
1930-529X
Type
conf
DOI
10.1109/GLOCOM.2012.6503420
Filename
6503420
Link To Document