Generalized Louvain method for community detection in large networks

International Conference on Intelligent Systems Design and Applications, ISDA

Volumn , Issue , 2011, Pages 88-93

  De Meo, Pasquale ^a   Ferrara, Emilio ^a   Fiumara, Giacomo ^a   Provetti, Alessandro ^a,b  

^a UNIVERSITY OF MESSINA   (Italy)

^b UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

community structure; complex networks

Indexed keywords

COMMUNITY DETECTION; COMMUNITY STRUCTURES; COMPLEX NETWORKS; LARGE NETWORKS; NEAR-LINEAR TIME; NETWORK MODULARITY; NOVEL STRATEGIES;

INTELLIGENT SYSTEMS; SOCIAL SCIENCES; SYSTEMS ANALYSIS;

ALGORITHMS;

EID: 84857613816     PISSN: 21647143     EISSN: 21647151     Source Type: Conference Proceeding    
DOI: 10.1109/ISDA.2011.6121636     Document Type: Conference Paper

References (21)

1. V. Blondel, J. Guillaume, R. Lambiotte, and E. Lefebvre, "Fast unfolding of communities in large networks," Journal of Statistical Mechanics: Theory and Experiment, p. P10008, 2008.
2. M. Porter, J. Onnela, and P. Mucha, "Communities in networks," Notices of the American Mathematical Society, vol. 56, no. 9, pp. 1082-1097, 2009.
3. S. Fortunato, "Community detection in graphs," Physics Reports, vol. 486, no. 3-5, pp. 75-174, 2010.
4. A. Ng, M. Jordan, and Y. Weiss, "On Spectral Clustering: Analysis and an algorithm," in Advances in Neural Information Processing Systems 14, 2001.
5. Y. Wei and C. Cheng, "Towards efficient hierarchical designs by ratio cut partitioning," in Proc. IEEE International Conference on Computer-Aided Design, 1989, pp. 298-301.
6. L. Hagen and A. Kahng, "New spectral methods for ratio cut partitioning and clustering," Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on, vol. 11, no. 9, pp. 1074-1085, 2002.
7. U. Brandes, D. Delling, M. Gaertler, R. Görke, M. Hoefer, Z. Nikoloski, and D. Wagner, "On finding graph clusterings with maximum modularity," in Graph-Theoretic Concepts in Computer Science, 2007, pp. 121-132.
8. M. Girvan and M. Newman, "Community structure in social and biological networks," PNAS, vol. 99, no. 12, p. 7821, 2002.
9. M. Newman and M. Girvan, "Finding and evaluating community structure in networks," Physical Review E, vol. 69, no. 2, p. 26113, 2004.
10. U. Brandes, "A faster algorithm for betweenness centrality, "Journal of Mathematical Sociology, vol. 25, no. 2, pp. 163-177, 2001.
11. A. Clauset, M. Newman, and C. Moore, "Finding community structure in very large networks," Physical Review E, vol. 70, no. 6, p. 66111, 2004.
12. J. Duch and A. Arenas, "Community detection in complex networks using extremal optimization," Physical Review E, vol. 72, no. 2, p. 27104, 2005.
13. M. Newman and E. Leicht, "Mixture models and exploratory analysis in networks," PNAS, vol. 104, no. 23, p. 9564, 2007.
14. M. Newman, "Finding community structure in networks using the eigenvectors of matrices," Physical Review E, vol. 74, no. 3, p. 36104, 2006.
15. E. Ferrara, P. De Meo, and G. Fiumara, "A novel measure of edge centrality in social networks," in under review, 2011.
16. A. Lancichinetti and F. Radicchi, "Benchmark graphs for testing community detection algorithms," Physical Review E, vol. 78, no. 4, p. 046110, 2008.
17. L. Danon, A. Diaz-Guilera, J. Duch, and A. Arenas, "Comparing community structure identification," Journal of Statistical Mechanics: Theory and Experiment, p. P09008, 2005.
18. S. Fortunato and M. Barthélemy, "Resolution limit in community detection," PNAS, vol. 104, no. 1, p. 36, 2007.
19. F. Radicchi, C. Castellano, F. Cecconi, V. Loreto, and D. Parisi, "Defining and identifying communities in networks,"PNAS, vol. 101, no. 9, p. 2658, 2004.
20. J. Leskovec and C. Faloutsos, "Sampling from large graphs,"in Proc. 12th ACM SIGKDD international conference on Knowledge discovery and data mining, 2006, pp. 631-636.
21. B. Viswanath, A. Mislove, M. Cha, and K. P. Gummadi, "On the evolution of user interaction in facebook," in Proc. 2nd ACM SIGCOMM Workshop on Social Networks, 2009.