Beyond Social Graphs: User Interactions in Online Social Networks and their Implications
Christo Wilson
Alessandra Sala
Krishna P. N. Puttaswamy
Ben Y. Zhao
ACM Transactions on the Web
Vol. 6, No. 4, Article 17, November 2012
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 present
in their social graph counterparts. This means that these graphs have
fewer "super-nodes" with extremely high degree, and overall graph
diameter increases significantly as a result. To quantify the impact of
our observations, we use both types of graphs to validate several
well-known social-based applications that rely on graph properties to
infuse new functionality into Internet applications, including Reliable
Email (RE), SybilGuard, and the weighted cascade influence maximization
algorithm.
The results reveal new insights into each of these systems, and confirm
our hypothesis that to obtain realistic and accurate results, ongoing
research on social network applications studies of social applications
should use real indicators of user interactions in lieu of social
graphs.