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 :
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