Robustness of social networks: Comparative results based on distance distributions

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6984 LNCS, Issue , 2011, Pages 8-21

  Boldi, Paolo ^a   Rosa, Marco ^a   Vigna, Sebastiano ^a  

^a UNIVERSITY OF MILAN   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

DATA SETS; DISTANCE DISTRIBUTIONS; LABEL PROPAGATION; NETWORK STRUCTURES; ORDERS OF MAGNITUDE; SOCIAL NETWORKS; WEB GRAPHS;

INFORMATION SCIENCE; SOCIAL NETWORKING (ONLINE); USER INTERFACES;

SOCIAL SCIENCES COMPUTING;

EID: 80054071589     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-24704-0_7     Document Type: Conference Paper

References (21)

1. Albert, R., Jeong, H., Barabasi, A.-L.: Error and attack tolerance of complex networks. Nature 406, 378-382 (2000)
2. Borgatti, S.P., Carley, K.M., Krackhardt, D.: On the robustness of centrality measures under conditions of imperfect data. Social Networks 28(2), 124-136 (2006)
3. Brandes, U., Erlebach, T. (eds.): Network Analysis. LNCS, vol. 3418, pp. 1-6. Springer, Heidelberg (2005)
4. Borgatti, S.P.: Centrality and network flow. Social Networks 27(1), 55-71 (2005)
5. Borgatti, S.P.: Identifying sets of key players in a social network. Comput. Math. Organ. Theory 12, 21-34 (2006)
6. Brandes, U.: A faster algorithm for betweenness centrality. Journal of Mathematical Sociology 25(2), 163-177 (2001)
7. Boldi, P., Rosa, M., Vigna, S.: HyperANF: Approximating the neighbourhood function of very large graphs on a budget. In: Proceedings of the 20th International Conference on World Wide Web, pp. 625-634. ACM, New York (2011)
8. Boldi, P., Santini, M., Vigna, S.: PageRank: Functional dependencies. ACM Trans. Inf. Sys. 27(4), 1-23 (2009)
9. Cohen, R., Havlin, S.: Complex Networks: Structure, Robustness and Function. Cambridge University Press, Cambridge (2010)
10. Chierichetti, F., Kumar, R., Lattanzi, S., Mitzenmacher, M., Panconesi, A., Raghavan, P.: On compressing social networks. In: KDD 2009, pp. 219-228. ACM, New York (2009)
11. Donato, D., Leonardi, S., Millozzi, S., Tsaparas, P.: Mining the inner structure of the web graph. Journal of Physics A: Mathematical and Theoretical 41(22), 224017 (2008)
12. Fogaras, D.: Where to Start Browsing the Web? In: Böhme, T., Heyer, G., Unger, H. (eds.) IICS 2003. LNCS, vol. 2877, pp. 65-79. Springer, Heidelberg (2003)
13. Li, L., Alderson, D.L., Doyle, J., Willinger, W.: Towards a theory of scale-free graphs: Definition, properties, and implications. Internet Math. 2(4) (2005)
14. Langville, A.N., Meyer, C.D.: Deeper inside PageRank. Internet Math. 1(3), 355-400 (2004)
15. Milgram, S.: The small world problem. Psychology Today 2, 60-67 (1967)
16. Marchiori, M., Latora, V.: Harmony in the small-world. Physica A 285(3- 4), 539-546 (2000)
17. Newman, M.E.J., Park, J.: Why social networks are different from other types of networks. Phys. Rev. E 68(3), 036122 (2003)
18. Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank citation ranking: Bringing order to the web. Technical report, Stanford Digital Library Technologies Project, Stanford University, USA (1998)
19. Palmer, C.R., Gibbons, P.B., Faloutsos, C.: Anf: a fast and scalable tool for data mining in massive graphs. In: KDD 2002, pp. 81-90. ACM, New York (2002)
20. Raghavan, U.N., Albert, R., Kumara, S.: Near linear time algorithm to detect community structures in large-scale networks. Phys. Rev. E 76(3) (2007)
21. Wasserman, S., Faust, K.: Social network analysis: Methods and applications. Cambridge Univ. Press, Cambridge (1994)