DMCA
Measuring the mixing time of social graphs (2010)
Cached
Download Links
| Citations: | 56 - 11 self |
BibTeX
@TECHREPORT{Mohaisen10measuringthe,
author = {Abedelaziz Mohaisen and Aaram Yun and Yongdae Kim},
title = {Measuring the mixing time of social graphs},
institution = {},
year = {2010}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
Social networks provide interesting algorithmic properties that can be used to bootstrap the security of distributed systems. For example, it is widely believed that social networks are fast mixing, and many recently proposed designs of such systems make crucial use of this property. However, whether real-world social networks are really fast mixing is not verified before, and this could potentially affect the performance of such systems based on the fast mixing property. To address this problem, we measure the mixing time of several social graphs, the time that it takes a random walk on the graph to approach the stationary distribution of that graph, using two techniques. First, we use the second largest eigenvalue modulus which bounds the mixing time. Second, we sample initial distributions and compute the random walk length required to achieve probability distributions close to the stationary distribution. Our findings show that the mixing time of social graphs is much larger than anticipated, and being used in literature, and this implies that either the current security systems based on fast mixing have weaker utility guarantees or have to be less efficient, with less security guarantees, in order to compensate for the slower mixing.
Keyphrases
mixing time social graph fast mixing social network stationary distribution algorithmic property random walk probability distribution eigenvalue modulus utility guarantee current security system several social graph initial distribution security guarantee distributed system fast mixing property crucial use real-world social network
