Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aggarwal C, Subbian K (2014) Evolutionary network analysis: a survey. ACM Comput Surv 47(1):10
Ahmad MA, Borbora Z, Srivastava J, Contractor NS (2010) Link prediction across multiple social networks. In: ICDM workshops. IEEE, Sydney, pp 911–918
Alon U (2007) Network motifs: theory and experimental approaches. Nat Rev Genet 8:450
Amaral LAN, Scala A, Barthélémy M, Stanley HE (2000) Classes of behavior of small-world networks. Proc Natl Acad Sci U S A 97:11149–11152
Araujo M, Papadimitriou S, Günnemann S, Faloutsos C, Basu P, Swami A, Koutra D (2014) Com2: fast automatic discovery of temporal (‘comet’) communities. In: PAKDD. Springer International Publishing, Tainan, pp 271–283
Barabási A, Albert R (1999) Emergence of scaling in random networks. Science 286:509–512
Bavelas A (1948) A mathematical model for group structures. Hum Organ 7:16–30
Bright DA, Hughes CE, Chalmers J (2012) Illuminating dark networks: a social network analysis of an Australian drug trafficking syndicate. Crime Law Soc Chang 57(2):151–176
Cai D, Shao Z, He X, Yan X, Han J (2005) Mining hidden community in heterogeneous social networks. In: Proceedings of the 3rd international workshop on link discovery. ACM, Chicago, IL, USA, pp 58–65
Cheng Z, Caverlee J, Barthwal H, Bachani V (2014) Who is the barbecue king of texas?: a geo-spatial approach to finding local experts on twitter. In: Proceedings of the 37th international ACM SIGIR, Gold Coast, pp 335–344
Clauset A, Moore C, Newman MEJ (2008) Hierarchical structure and the prediction of missing links in networks. Nature 453:98
Coleman J, Katza E, Menzel H (1957) The diffusion of an innovation among physicians. Sociometry 20:253–270
Dodds PS, Watts DJ (2005) A generalized model of social and biological contagion. J Theor Biol 232:587–604
Domingos P, Richardson M (2001) Mining the network value of customers. In: Proceedings of the seventh ACM SIGKDD international conference on knowledge discovery and data mining (KDD). San Francisco
Dunlavy DM, Kolda TG, Acar E (2011) Temporal link prediction using matrix and tensor factorizations. ACM Trans Knowl Discov Data 5(2):10
Freeman LC (1979) Centrality in social networks: I. Conceptual clarification. Soc Netw 1:215–239
Gilbert E, Karahalios K (2009) Predicting tie strength with social media. In: CHI ‘09. ACM, Boston
Goldenberg J, Libai B, Muller E (2001a) Using complex systems analysis to advance marketing theory development: modeling heterogeneity effects on new product growth through stochastic cellular automata. Acad Mark Sci Rev [Online] 1(9):1–20
Goldenberg J, Libai B, Muller E (2001b) Talk of the network: a complex systems look at the underlying process of word-of-mouth. Mark Lett 12(3):209–221
Goyal A, Bonchi F, Lakshmanan LV (2011) A data-based approach to social influence maximization. Proc VLDB Endowment 5(1):73–84
Gregory S (2007) An algorithm to find overlapping community structure in networks. In: Knowledge discovery in databases. PKDD 2007. Springer Berlin Heidelberg, Warsaw, pp 91–102
Guo G, Zhang J, Yorke-Smith N (2015). TrustSVD: collaborative filtering with both the explicit and implicit influence of user trust and of item ratings. In: AAAI Press, pp 123–129
Gupta, M, Gao, J, Sun, Y, Han, J (2012). Integrating community matching and outlier detection for mining evolutionary community outliers. In: Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining. Beijing, China
Hasan M, Chaoji V, Salem S, Zaki M (2005) Link prediction using supervised learning. In: Proceedings of the workshop on link discovery: issues, approaches and applications. Society for Industrial and Applied Mathematics, Bethedsa, MD, USA
Haveliwala TH (2003) Topic-sensitive PageRank: a context-sensitive ranking algorithm for web search. IEEE Trans Knowl Data Eng 15(4):784–796
Haveliwala T, Kamvar S, Jeh G (2003) An analytical comparison of approaches to personalizing PageRank (technical report). Stanford University, Stanford
Huang, F, Niranjan, UN, Hakeem, MU, Anandkumar A (2013) Fast detection of overlapping communities via online tensor methods. arXiv preprint arXiv:1309.0787
Immorlica N, Kleinberg J, Mahdian M, Wexler T (2007) The role of compatibility in the diffusion of technologies through social networks. In: Proceedings of the eighth ACM conference on electronic commerce (EC). ACM, San Diego
Kapoor K, Sharma D, Srivastava J (2013) Weighted node degree centrality for hypergraphs. In: Network Science Workshop (NSW), 2013 I.E. 2nd. IEEE, West Point, NY, USA, pp 152–155
Keegan B, Ahmed M, Williams D, Srivastava J, Contractor N (2010) Dark gold: statistical properties of clandestine networks in massively multiplayer online games. In: SocialCom 10. Minneapolis, pp 201–208
Kempe D, Kleinberg J, Tardos E (2003) Maximizing the spread of influence in a social network. In: Proceedings of the ninth ACM SIGKDD international conference on knowledge discovery and data mining (KDD). ACM, Washington, DC
Kempe D, Kleinberg J, Tardos E (2005) Influential nodes in a diffusion model for social networks. In: Proceedings of the 32nd international colloquium on automata, languages and programming (ICALP). Springer Berlin Heidelberg, Lisbon
Kleinberg J (1998) Authoritative sources in a hyperlinked environment. In: Proceedings of the ACM-SIAM symposium on discrete algorithms. ACM, San Francisco
Knoke D, Burt RS (1983) Prominence. In: Burt RS, Minor MJ (eds) Applied network analysis. Sage, Newbury Park, pp 195–222
Kochen M (1989) Preface. In: Kochen M (ed) The small world. Ablex, Norwood, pp vii–xiii
Kostka J, Oswald YA, Wattenhofer R (2008) Word of mouth: rumor dissemination in social networks. In: 15th international colloquium on structural information and communication complexity (SIROCCO). Springer Berlin Heidelberg, Villars-sur-Ollon, Switzerland, June 2008
Lappas T, Liu K, Terzi E (2011) A survey of algorithms and systems for expert location in social networks. Social Network Data Analytics. Springer US, pp 215–241
Leskovec J, Adamic LA, Huberman BA (2006a) The dynamics of viral marketing. In: Proceedings of the 7th ACM conference on electronic commerce. ACM, Ann Arbor
Leskovec J, Singh A, Kleinberg J (2006b) Patterns of influence in a recommendation network. In: Pacific-Asia conference on knowledge discovery and data mining (PAKDD). Singapore
Leskovec J, Huttenlocher D, Kleinberg J (2010) Predicting positive and negative links in online social networks. In: Proceedings of WWW’2010. ACM, New York
Leung A, Dron W, Hancock JP, Aguirre M, Purnell J, Han J, Wang C, Srivastava J, Mahapatra A, Roy A, Scott L (2013) Social patterns: community detection using behavior-generated network datasets. In: Network Science Workshop (NSW), 2013 I.E. 2nd. IEEE, West Point, NY, USA, pp 82–89.
Liben-Nowell D, Kleinberg J (2007) The link-prediction problem for social networks. J Am Soc Inf Sci Technol 58:1019
Liggett TM (1985) Interacting particle systems. Springer, New York
Liu L, Tang J, Han J, Yang S (2012) Learning influence from heterogeneous social networks. Data Min Knowl Disc 25(3):511–544
Liu Z, He JL, Kapoor K, Srivastava J (2013) Correlations between community structure and link formation in complex networks. PLoS One 8(9):e72908
Lü L, Zhou T (2010) Link prediction in weighted networks: the role of weak ties. EPL 89:18001
Morris S (2000) Contagion. The Review of Economic Studies 67(1):57–78.
Myers S, Zhu C, Leskovec J (2012) Information diffusion and external influence in networks. In: Proceedings of the 18th ACM SIGKDD. Beijing, pp 33–41
Page L, Brin S, Motwani R, Winograd T (1998) The PageRank citation ranking: bringing order to the web. In: Stanford digital libraries working paper, Stanford InfoLab
Palla G, Derényi I, Farkas I, Vicsek T (2005) Uncovering the overlapping community structure of complex networks in nature and society. Nature 435(7043):814–818
Pathak N, Delong C, Banerjee A, Erickson K (2008) Social topic models for community extraction. In: The 2nd SNA-KDD workshop ’08 (SNA-KDD’08). ACM, Las Vegas
Qin J, Xu JJ, Hu D, Sageman M, Chen H (2005) Analyzing terrorist networks: a case study of the global Salafi Jihad network. In: Intelligence and security informatics. Springer Berlin Heidelberg, Atlanta
Roy A. (2015) Computational trust at various granularities in social networks. Doctoral dissertation, University of Minnesota
Roy A, Sarkar C, Srivastava J, Huh J (2016) Trustingness & trustworthiness: a pair of complementary trust measures in a social network. In: Advances in Social Networks Analysis and Mining (ASONAM), 2016 IEEE/ACM International Conference on. IEEE, San Francisco, CA, USA, pp 549–554
Sewell DK, Chen Y (2015) Latent space models for dynamic networks. J Am Stat Assoc 110(512):1646–1657
Steyvers M, Smyth P, Rosen-Zvi M, Griffiths T (2004) Probabilistic author-topic models for information discovery. In: Proceedings of 10th ACM SIGKDD. Seattle, pp 306–315
Subbian K, Aggarwal C, Srivastava J (2016) Mining influencers using information flows in social streams. ACM Trans Knowl Disc Data 10(3):26
Tantipathananandh C, Berger-Wolf TY, Kempe D (2007) A framework for community identification in dynamic social networks. In: SIGKDD international conference on knowledge discovery and data mining. San Jose, pp 717–726
Travers J, Milgram S (1969) An experimental study of the small world problem. Sociometry 32:425–443
Tylenda T, Angelova R, Bedathur S (2009) Towards time-aware link prediction in evolving social networks. In: Proceedings of the 3rd workshop on social network mining and analysis. ACM, Paris/New York
Walter FE, Battiston S, Schweitzer F (2008) A model of a trust-based recommendation system of a social network. Auton Agents Multi-Agent Syst 16:57–74
Wasserman S, Faust K (1994) Social network analysis. Cambridge University Press, Cambridge
Watts DJ, Dodds PS (2007) Influentials, networks, and public opinion formation. J Consum Res 34:441–458
Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393:409–410
Williams D, Poole S, Contractor N, Srivastava J (2011) The virtual world exploratorium: using large-scale data and computational techniques for communication research. Commun Methods Meas 5:163–180
Xiang R, Neville J, Rogati M (2009) Modeling relationship strength in online social networks. In: Workshop on analyzing networks and learning with graphs. Whistler, Dec 2009
Yap HY, Lim TM (2016) Trusted social node: evaluating the effect of trust and trust variance to maximize social influence in a multilevel social node influential diffusion model. In: International Conference on Computational Science and Its Applications. Springer, pp 530–542
Yu K, Chu W, Yu S, Tresp V, Xu Z (2006) Stochastic relational models for discriminative link prediction. In: Proceedings of neural information processing systems. MIT, Cambridge, p 1553
Zhang J, Tang J, Li J-Z (2007) Expert finding in a social network. In: Proceedings of DASFAA’2007. Bangkok, pp 1066–1069
Zhao Y, Levina E, Zhu J (2011) Community extraction for social networks. In: Proceedings of the 2011 joint statistical meetings. Miami Beach
Zhou D, Manavoglu E, Li J, Giles CL, Zha H. (2006) Probabilistic models for discovering e-communities. In Proceedings of the 15th international conference on World Wide Web, 2006. ACM, New York, pp 173–182.
Zhu L, Guo D, Yin J, Ver Steeg G, Galstyan A (2016) Scalable temporal latent space inference for link prediction in dynamic social networks. IEEE Trans Knowl Data Eng 28(10):2765–2777
Recommended Reading
Elsner U (1997) Graph partitioning: a survey. Technical report 97–27. Technische Universität Chemnitz, Chemnitz
Fortunato S (2010) Community detection in graphs. Phys Rep 486:75–174
Kleinberg J (2007) Cascading behavior in networks: algorithmic and economic issues. In: Algorithmic game theory. Cambridge University Press, Cambridge, pp 613–632
Wortman J (2008) Viral marketing and the diffusion of trends on social networks, technical reports, MS-CIS-08-19, Department of Computer and Information Science, University of Pennsylvania
Acknowledgments
We hereby acknowledge all the past and present members of the Data Mining Research Lab at the University of Minnesota, Twin Cities, namely, Aarti Sathyanarayana, Ankit Sharma, Bhavtosh Rath, Kartik Singhal, Kyong Jin Shim, Muhammad Ahmad, Nishith Pathak, Colin DeLong, Amogh Mahapatra, Zoheb Borbora, Atanu Roy, and Chandrima Sarkar.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media LLC, part of Springer Nature
About this entry
Cite this entry
Aggarwal, K., Kapoor, K., Srivastava, J. (2018). Data Mining Techniques for Social Networks Analysis. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7131-2_56
Download citation
DOI: https://doi.org/10.1007/978-1-4939-7131-2_56
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4939-7130-5
Online ISBN: 978-1-4939-7131-2
eBook Packages: Computer ScienceReference Module Computer Science and Engineering