DocumentCode
1826938
Title
Determining credibility from social network structure
Author
Briscoe, Erica J. ; Appling, D. Scott ; Mappus, Rudolph L. ; Hayes, Heather
Author_Institution
Georgia Inst. of Technol., Georgia Tech Res. Inst., Atlanta, GA, USA
fYear
2013
fDate
25-28 Aug. 2013
Firstpage
1418
Lastpage
1424
Abstract
The increasing proliferation of social media results in users that are forced to ascertain the truthfulness of information that they encounter from unknown sources using a variety of indicators (e.g. explicit ratings, profile information, etc.). Through human-subject experimentation with an online social network-style platform, our study focuses on the determination of credibility in ego-centric networks based on subjects observing social network properties such as degree centrality and geodesic distance. Using manipulated social network graphs, we find that corroboration and degree centrality are most utilized by subjects as indicators of credibility. We discuss the implications of the use of social network graph structural properties and use principal components analysis to visualize the reduced dimensional space.
Keywords
data visualisation; graph theory; principal component analysis; social networking (online); corroboration; credibility determination; data visualization; degree centrality; ego-centric networks; geodesic distance; human-subject experimentation; information truthfulness; online social network-style platform; principal components analysis; social media; social network graph structural properties; social network structure; Conferences; Context; Instruction sets; Media; Message systems; Principal component analysis; Social network services; credibility; ego-centric networks; human experimentation; social media; social networks; structural properties; trust;
fLanguage
English
Publisher
ieee
Conference_Titel
Advances in Social Networks Analysis and Mining (ASONAM), 2013 IEEE/ACM International Conference on
Conference_Location
Niagara Falls, ON
Type
conf
Filename
6785889
Link To Document