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Graphs over time: densification laws, shrinking diameters and possible explanations
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Structure and evolution of online social networks
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Graph evolution: Densification and shrinking diameters
ACM Transactions on Knowledge Discovery from Data (TKDD)
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Fast Counting of Triangles in Large Real Networks without Counting: Algorithms and Laws
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
On the evolution of user interaction in Facebook
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Predicting positive and negative links in online social networks
Proceedings of the 19th international conference on World wide web
Proceedings of the 19th international conference on World wide web
Expansion and search in networks
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Rumour spreading and graph conductance
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
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Social network analysis has become an extremely popular research area, where the main focus is the understanding of networks' structure. In this paper, we study the expansibility of large social graphs, a structural property based on the notion of expander graphs (i.e. sparse graphs with strong connectivity properties). It is widely believed that social networks have poor expansion properties, due to their communitybased organization. Moreover, this was experimentally confirmed on small scale networks and it is considered as a global property of social networks (independent of the graph's size) in many applications. What really happens in large scale social graphs? To address this question, we measure the expansion properties of several large scale social graphs using the measure of subgraph centrality. Our findings show a clear difference on the expansibility between small and large scale social networks, and thus structural differences. Our observations could be utilized in a range of applications which are based on social graphs' structure.