User Recognition From Social Behavior in Computer-Mediated Social Context | IEEE Journals & Magazine | IEEE Xplore

User Recognition From Social Behavior in Computer-Mediated Social Context


Abstract:

Social interactions are integral part of human behavior. Although social interactions are likely to possess unique behavioral patterns, their significance for automated u...Show More

Abstract:

Social interactions are integral part of human behavior. Although social interactions are likely to possess unique behavioral patterns, their significance for automated user recognition has been noted in the scientific community only recently. This paper demonstrated that it is possible to generate a set of unique features, called social behavioral (SB) features, from the social interactions of individuals' via an online social network (OSN). Specifically, this research identified a set of SB features from the online social interactions of 241 Twitter users and proposed a framework to utilize these features for an automated user recognition. Extensive experimentation demonstrated high recognition performance as well as distinctiveness of the proposed SB features. The most striking finding was that only ten recent tweets are enough to recognize 58% of users in our database at rank-1. The rank-1 recognition rate dramatically increased to 93% when 60 tweets were used as a probe set. Experimental results also demonstrated the stability of the proposed SB feature set over time and ability to recognize both frequent and nonfrequent OSN users. This confirms that human social behavior expressed through an OSN can provide a unique insight into user behavior recognition.
Published in: IEEE Transactions on Human-Machine Systems ( Volume: 47, Issue: 3, June 2017)
Page(s): 356 - 367
Date of Publication: 03 April 2017

ISSN Information:

Funding Agency:


References

References is not available for this document.