User Interactions in Social Networks and their Implications
Christo Wilson
Bryce Boe
Alessandra Sala
Krishna P. N. Puttaswamy
Ben Y. Zhao
ACM EuroSys 2009
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Paper Abstract
Social networks are popular platforms for interaction, communication and collaboration between friends. Researchers have recently proposed an emerging class of applications that leverage relationships from social networks to improve security and performance in applications such as email, web browsing and overlay routing. While these applications often cite social network connectivity statistics to support their designs, researchers in psychology and sociology have repeatedly cast doubt on the practice of inferring meaningful relationships from social network connections alone. This leads to the question: Are social links valid indicators of real user interaction? If not, then how can we quantify these factors to form a more accurate model for evaluating socially-enhanced applications?
In this paper, we address this
question through a detailed study of user interactions in the Facebook
social network. We propose the use of interaction graphs to
impart meaning to online social links by quantifying user
interactions. We analyze interaction graphs derived from Facebook user
traces and show that they exhibit significantly lower levels of the
"small-world" properties shown in their social graph counterparts. This
means that these graphs have fewer "supernodes" with extremely high
degree, and overall network diameter increases significantly as a
result. To quantify the impact of our observations, we use both types of
graphs to validate two well-known social-based applications (RE
and SybilGuard). The results reveal new insights into both systems, and
confirm our hypothesis that studies of social applications should use
real indicators of user interactions in lieu of social graphs.