Topological sorting of large networks
Communications of the ACM
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
On unbiased sampling for unstructured peer-to-peer networks
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Analysis of topological characteristics of huge online social networking services
Proceedings of the 16th international conference on World Wide Web
Parallel crawling for online social networks
Proceedings of the 16th international conference on World Wide Web
Proceedings of the first workshop on Online social networks
Growth of the flickr social network
Proceedings of the first workshop on Online social networks
The convergence of social and technological networks
Communications of the ACM - Remembering Jim Gray
MEK: Using spatial-temporal information to improve social networks and knowledge dissemination
Information Sciences: an International Journal
APWEB '10 Proceedings of the 2010 12th International Asia-Pacific Web Conference
Walking in facebook: a case study of unbiased sampling of OSNs
INFOCOM'10 Proceedings of the 29th conference on Information communications
Reducing large internet topologies for faster simulations
NETWORKING'05 Proceedings of the 4th IFIP-TC6 international conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communication Systems
Bridge analysis in a Social Internetworking Scenario
Information Sciences: an International Journal
Crawling Social Internetworking Systems
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
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In new generation social networks, we expect that the paradigm of Social Internetworking Systems (SISs) will become progressively more important. Indeed, the possibility of interconnecting users and resources of different social networks enables a lot of strategic applications whose main strength is the integration of different communities that nevertheless preserves their diversity and autonomy. In this new scenario, the role of Social Network Analysis is crucial in studying the evolution of structures, individuals, interactions, and so on, and in extracting powerful knowledge from them. But the preliminary step to do is designing a good way to crawl the underlying graph. Although this aspect has been deeply investigated in the field of social networks, it is an open issue when moving towards SISs. Indeed, we cannot expect that a crawling strategy, specifically designed for social networks, is still valid in a Social Internetworking Scenario, due to its specific topological features. In this paper, we confirm the above claim, giving a strong motivation for our second contribution, which is the definition of a new crawling strategy. This strategy, specifically conceived for SISs, is shown to fully overcome the drawbacks of the state-of-the-art crawling strategies.