Structure and evolution of online social networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the first workshop on Online social networks
Hot today, gone tomorrow: on the migration of MySpace users
Proceedings of the 2nd ACM workshop on Online social networks
Counting YouTube videos via random prefix sampling
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Coarse-grained topology estimation via graph sampling
Proceedings of the 2012 ACM workshop on Workshop on online social networks
Are All Social Networks Structurally Similar?
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Google+ or Google-?: dissecting the evolution of the new OSN in its first year
Proceedings of the 22nd international conference on World Wide Web
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While the size of popular online social networks such as MySpace and Twitter has been reported to be in the tens or hundreds of millions of users (and growing), little is known about the fraction of users who have either deleted or abandoned their accounts. Therefore, the growth of an OSN's overall user population and, more important, its population of active users cannot easily be determined. In this article we describe a measurement technique to infer the fine-grained growth in the total number of allocated accounts for a class of OSNs that include MySpace and Twitter and are characterized by two features. First, they assign numerical user IDs using a format and allocation strategy that can be determined. Second, a fraction of their users have abandoned these OSNs shortly after creating their accounts, and these short-lived users (called "tourists") are scattered across the ID space. By exploiting these two properties, we are able to determine the growth in total and valid user accounts for MySpace and Twitter since their inception. For valid user accounts, we also derive the fraction of active users in the system at the time of our experiment, where we define the activity of a user in terms of the recency of her last visit to the OSN. In the case of MySpace and Twitter, our results show that the active population of these OSNs is typically an order of magnitude smaller than the reported (total) population.