L. Adamic and E. Adar, Friends and neighbors on the Web, Social Networks, vol.25, issue.3, pp.211-230, 2001.
DOI : 10.1016/S0378-8733(03)00009-1

E. Behrends, Introduction to Markov Chains with Special Emphasis on Rapid Mixing, Advanced Lectures in Mathematics, 2000.

V. D. Blondel, J. Guillaume, R. Lambiotte, and E. Lefebvre, Fast unfolding of communities in large networks, Journal of Statistical Mechanics: Theory and Experiment, vol.2008, issue.10, p.10008, 2008.
DOI : 10.1088/1742-5468/2008/10/P10008
URL : https://hal.archives-ouvertes.fr/hal-01146070

Y. Boshmaf, D. Logothetis, G. Siganos, J. Lería, J. Lorenzo et al., Integro: Leveraging Victim Prediction for Robust Fake Account Detection in OSNs, Proceedings 2015 Network and Distributed System Security Symposium, 2015.
DOI : 10.14722/ndss.2015.23260

Y. Boshmaf, I. Muslukhov, K. Beznosov, and M. Ripeanu, The socialbot network, Proceedings of the 27th Annual Computer Security Applications Conference on, ACSAC '11, pp.93-102, 2011.
DOI : 10.1145/2076732.2076746

Q. Cao, M. Sirivianos, X. Yang, and T. Pregueiro, Aiding the Detection of Fake Accounts in Large Scale Social Online Services, Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation, pp.15-15, 2012.

W. Chang and J. Wu, Survey of Sybil Attacks in Networks
DOI : 10.1201/b17124-28

S. Cresci, R. D. Pietro, M. Petrocchi, A. Spognardi, and M. Tesconi, Fame for sale: Efficient detection of fake Twitter followers, Decision Support Systems, vol.80, pp.56-71, 2015.
DOI : 10.1016/j.dss.2015.09.003

G. Danezis and P. Mittal, Sybilinfer: Detecting Sybil Nodes Using Social Networks, NDSS, 2009.

M. Dellamico and Y. Roudier, A Measurement of Mixing Time in Social Networks, Proceedings of the 5th International Workshop on Security and Trust Management, 2009.

N. B. Ellison, Social Network Sites: Definition, History, and Scholarship, Journal of Computer-Mediated Communication, vol.13, issue.1, pp.210-230, 2007.

X. Feng, J. Zhao, and K. Xu, Link prediction in complex networks: a clustering perspective, The European Physical Journal B, vol.79, issue.1, pp.1-9, 2012.
DOI : 10.1140/epjb/e2011-20207-x

M. Fire, L. Tenenboim-chekina, R. Puzis, O. Lesser, L. Rokach et al., Computationally efficient link prediction in a variety of social networks, ACM Transactions on Intelligent Systems and Technology, vol.5, issue.1, p.10, 2013.
DOI : 10.1145/2542182.2542192

H. Gao, J. Hu, C. Wilson, Z. Li, Y. Chen et al., Detecting and Characterizing Social Spam Campaigns, Proceedings of the 10th ACM SIGCOMM conference on Internet measurement, pp.35-47, 2010.

P. Gao, N. Z. Gong, S. Kulkarni, K. Thomas, and P. Mittal, Sybilframe: A Defense-in-Depth Framework for Structure-Based Sybil Detection. arXiv preprint, 2015.

S. Ghosh, B. Viswanath, F. Kooti, N. K. Sharma, G. Korlam et al., Understanding and combating link farming in the twitter social network, Proceedings of the 21st international conference on World Wide Web, WWW '12, pp.61-70, 2012.
DOI : 10.1145/2187836.2187846

J. Golbeck, Trust and nuanced profile similarity in online social networks, ACM Transactions on the Web, vol.3, issue.4, p.12, 2009.
DOI : 10.1145/1594173.1594174

G. H. Golub, H. A. Van, and . Vorst, Eigenvalue computation in the 20th century, Journal of Computational and Applied Mathematics, vol.123, issue.1-2, pp.35-65, 2000.
DOI : 10.1016/S0377-0427(00)00413-1

C. Grier, K. Thomas, V. Paxson, and M. Zhang, @spam, Proceedings of the 17th ACM conference on Computer and communications security, CCS '10, pp.27-37, 2010.
DOI : 10.1145/1866307.1866311

I. Kahanda and J. Neville, Using Transactional Information to Predict Link Strength in, Online Social Networks. ICWSM, vol.9, pp.74-81, 2009.

J. Leskovec, K. J. Lang, A. Dasgupta, and M. W. Mahoney, Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters, Internet Mathematics, vol.6, issue.1, pp.29-123, 2009.
DOI : 10.1080/15427951.2009.10129177

R. N. Lichtenwalter, J. T. Lussier, and N. V. Chawla, New perspectives and methods in link prediction, Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '10, pp.243-252, 2010.
DOI : 10.1145/1835804.1835837

A. Mohaisen, A. Yun, and Y. Kim, Measuring the mixing time of social graphs, Proceedings of the 10th annual conference on Internet measurement, IMC '10, pp.383-389, 2010.
DOI : 10.1145/1879141.1879191

S. Nagaraja, Anonymity in the Wild: Mixes on Unstructured Networks, Privacy Enhancing Technologies, pp.254-271, 2007.
DOI : 10.1007/978-3-540-75551-7_16

M. E. Newman and M. Girvan, Finding and evaluating community structure in networks, Physical Review E, vol.69, issue.2, p.26113, 2004.
DOI : 10.1103/PhysRevE.69.026113

L. Shi, S. Yu, W. Lou, and Y. T. Hou, SybilShield: An agent-aided social network-based Sybil defense among multiple communities, 2013 Proceedings IEEE INFOCOM, pp.1034-1042, 2013.
DOI : 10.1109/INFCOM.2013.6566893

T. Stein, E. Chen, and K. Mangla, Facebook immune system, Proceedings of the 4th Workshop on Social Network Systems, SNS '11, p.8, 2011.
DOI : 10.1145/1989656.1989664

G. Stringhini, C. Kruegel, and G. Vigna, Detecting spammers on social networks, Proceedings of the 26th Annual Computer Security Applications Conference on, ACSAC '10, pp.1-9, 2010.
DOI : 10.1145/1920261.1920263

K. Thomas, C. Grier, D. Song, and V. Paxson, Suspended accounts in retrospect, Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference, IMC '11, pp.243-258, 2011.
DOI : 10.1145/2068816.2068840

J. C. Valverde-rebaza, A. De-andrade, and . Lopes, Link Prediction in Complex Networks Based on Cluster Information, Advances in Artificial Intelligence-SBIA 2012, pp.92-101, 2012.
DOI : 10.1007/978-3-642-34459-6_10

A. H. Wang, Don'T Follow Me: Spam Detection in Twitter, Security and Cryptography (SECRYPT) Proceedings of the 2010 International Conference on, pp.1-10, 2010.

G. Yan, G. Chen, S. Eidenbenz, and N. Li, Malware propagation in online social networks, Proceedings of the 6th ACM Symposium on Information, Computer and Communications Security, ASIACCS '11, pp.196-206, 2011.
DOI : 10.1145/1966913.1966939

Z. Yang, C. Wilson, X. Wang, T. Gao, B. Y. Zhao et al., Uncovering Social Network Sybils in the Wild, ACM Transactions on Knowledge Discovery from Data (TKDD), vol.8, issue.12, 2014.

F. Yao and L. Chen, Similarity propagation based link prediction in bipartite networks, Network Security and Communication Engineering: Proceedings of the 2014 International Conference on Network Security and Communication Engineering, p.295, 2014.
DOI : 10.1201/b18660-65

H. Yu, Sybil defenses via social networks, ACM SIGACT News, vol.42, issue.3, pp.80-101, 2011.
DOI : 10.1145/2034575.2034593

H. Yu, P. B. Gibbons, M. Kaminsky, and F. Xiao, Sybillimit: A Near-Optimal Social Network Defense against Sybil Attacks, Security and Privacy, pp.3-17, 2008.

H. Yu, M. Kaminsky, P. B. Gibbons, and A. D. Flaxman, SybilGuard: Defending Against Sybil Attacks via Social Networks, IEEE/ACM Transactions on Networking, vol.16, issue.3, pp.576-589, 2008.
DOI : 10.1109/TNET.2008.923723

X. Zhao, L. Li, and G. Xue, Authenticating Strangers in Fast Mixing Online Social Networks, Global Telecommunications Conference, pp.1-5, 2011.