Abstract
Social network analysis attracted interests from both the research and business communities for a strong potential and variety of applications. In addition, this interest has been fuelled by the large success of online social networking sites and the subsequent abundance of social network data produced. A key aspect in this research field is the influence maximization in social networks. In this paper we discuss an overview about the models and the approaches widely used to analyse social networks. In this context, we also discuss data preparation and privacy concerns also considering different kind of approaches based on centrality measures.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Degene, A., Forse, M.: Introducing Social Networks. SAGE Publications, Thousand Oaks (1999)
Scott, J.: Social Network Analysis: A Handbook. SAGE Publications, Thousand Oaks (2000)
Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge (1994)
Fawcett, T., Provost, F.: Adaptive fraud detection. Data Min. Knowl. Discov. 1(3), 291–316 (1997)
Eagle, N., Pentland, A.S.: Reality mining: sensing complex social systems. Pers. Ubiquitous Comput. 10(4), 255–268 (2006)
Cuomo, S., De Michele, P., Piccialli, F., Galletti, A., Jung, J.E.: IoT-based collaborative reputation system for associating visitors and artworks in a cultural scenario. Expert Syst. Appl. 79, 101–111 (2017)
Buskens, V.: The social structure of trust. Soc. Netw. 20(3), 265–289 (1998)
Chianese, A., Marulli, F., Moscato, V., Piccialli, F.: A “smart” multimedia guide for indoor contextual navigation in cultural heritage applications. In: Paper presented at: International Conference on Indoor Positioning and Indoor Navigation, Montbeliard-Belfort, France (2013)
Cuomo, S., De Michele, P., Pragliola, M.: A computational scheme to predict dynamics in IoT systems by using particle filter. Concurr. Comput. Pract. Exp. 29(11), e4101 (2017)
Chianese, A., Piccialli, F., Riccio, G.: Designing a smart multisensor framework based on Beaglebone black board. In: Computer Science and Its Applications. Lecture Notes in Electrical Engineering, vol. 330, pp. 391–397. Springer, Berlin (2015)
Chianese, A., Piccialli, F.: SmaCH: a framework for smart cultural heritage spaces. In: Paper presented at: 2014 Tenth International Conference on Signal-Image Technology and Internet-Based Systems, Marrakech, Morocco (2015)
Hong, M., Jung, J., Piccialli, F., Chianese, A.: Social recommendation service for cultural heritage. Pers. Ubiquit. Comput. 21(2), 191–201 (2017)
Ferlez, J., Faloutsos, C., Leskovec, J., Mladenic, D., Grobelnik, M.: Monitoring network evolution using MDL. In: Paper Presented at: 2008 IEEE 24th International Conference on Data Engineering, Cancun, Mexico (2008)
Ostfeld, A., Salomons, E.: Optimal layout of early warning detection stations for water distribution systems security. J. Water Resour. Plan. Manage. 130(5), 377–385 (2004)
Ostfeld, A., Uber, J., Salomons, E., et al.: The battle of the water sensor networks (BWSN): a design challenge for engineers and algorithms. J. Water Resour. Plan. Manage. 134(6), 556–568 (2008)
Freeman, L.: The development of social network analysis. A Study in the Sociology of Science, vol. 1 (2004)
Coleman, J., Katz, E., Menzel, H.: Medical innovations: a diffusion study. Soc. Forces 46(2), 291 (1966)
Kuss, D.J., Griffiths, M.D.: Online social networking and addiction: a review of the psychological literature. Int. J. Environ. Res. Public Health 8(9), 3528–3552 (2011)
“Time spent” on these sites growing three times faster than overall internet rate, now accounting for almost 10 percent of all internet time. Nielsen Web site (2009). http://www.nielsen.com/us/en/press-room/2009/social-networks–.html
Rahm, E., Do, H.H.: Data cleaning: problems and current approaches. IEEE Data Eng. Bull. 23(4), 3–13 (2000)
Evfimievski, A., Srikant, R., Agrawal, R., Gehrke, J.: Privacy preserving mining of association rules. Inf. Syst. 29(4), 343–364 (2002)
Evfiemski, A., Geherke, J., Srikant, R.: Limiting privacy breaches in privacy preserving data mining. In: Proceedings of the Twenty-Second ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS 2003, San Diego, CA (2003)
Backstorm, L., Dwork, C., Kleinberg, J.: Anonymized social networks, hidden patterns, and structural steganography. In: Proceedings of the 16th International Conference on World Wide Web, WWW 2007, Banff, Canada (2007)
Dalenius, T.: Towards a methodology for statistical disclosure control. Statistik Tidskrift. 15, 429–444 (1977)
Kempe, D., Kleinberg, J., Tardos, É.: Maximizing the spread of influence through a social network. In: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2003, Washington, DC (2003)
Blum, A., Dwork, C., McSherry, F., Nissim, K.: Practical privacy: the SuLQ framework. In: Proceedings of the Twenty-Fourth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS 2005, Baltimore, MD (2005)
Aggarwal, G., Mishra, N., Pinkas, B.: Secure computation of the kth-ranked element. In: Advances in Cryptology - EUROCRYPT 2004. Lecture Notes in Computer Science. Springer, Heidelberg (2004)
Agrawal, R., Srikant, R.: Privacy-preserving data mining. In: Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data, SIGMOD 2000, Dallas, TX (2000)
Lappas, T., Liu, K., Terzi, E.: Finding a team of experts in social networks. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2009, Paris, France (2008)
Wu, W., Xiao, Y., Wang, W., He, Z., Wang, Z.: K-symmetry model for identity anonymization in social networks. In: Proceedings of the 13th International Conference on Extending Database Technology, EDBT 2010, Lausanne, Switzerland (2010)
Hanhijarvi, S., Garriga, G.C., Puolamäki, K.: Randomization techniques for graphs. In: Proceedings of the 2009 SIAM International Conference on Data Mining. Sparks, NV (2009)
Hay, M., Miklau, G., Jensen, D., Weis, P., Srivastava, S.: Anonymizing social networks. Technical report. University of Massachusetts Amherst, Amherst (2007)
Campan, A., Truta, T.M.: A clustering approach for data and structural anonymity in social networks. In: Paper presented at: 2nd ACM SIGKDD International Workshop on Privacy, Security, and Trust in KDD, Las Vegas, NV (2008)
Hay, M., Miklau, G., Jensen, D., Towsley, D., Weis, P.: Resisting structural re-identification in anonymized social networks. Proc. VLDB Endow. 1(1), 102–114 (2008)
Zheleva, E., Getoor, L.: Preserving the privacy of sensitive relationships in graph data. In: Privacy, Security, and Trust in KDD. Springer, Berlin (2007)
Ž urauskiene, J., Kirk, P.D.W., Stumpf, M.P.H.: A graph theoretical approach to data fusion. bioRxiv preprint (2015)
Bauer, F., Lizier, J.T.: Identifying influential spreaders and efficiently estimating infection numbers in epidemic models: a walk counting approach. Europhys. Lett. 99(6), 68007 (2012)
Lawyer, G.: Understanding the spreading power of all nodes in a network: a continuous-time perspective. Proc. Natl. Acad. Sci. 9, 1–7 (2015). https://arxiv.org/pdf/1405.6707.pdf
Centrality. Wikipedia Web site (2017). https://en.wikipedia.org/wiki/Centrality
Bonacich, P.: Power and centrality: a family of measures. Am. J. Sociol. 92(5), 1170–1182 (1987)
Borgatti, S.P.: Centrality and network flow. Soc Netw. 27, 55–71 (2005)
Amato, F., Moscato, F.: Exploiting cloud and workflow patterns for the analysis of composite cloud services. Future Gener. Comput. Syst. 67, 255–265 (2017)
Amato, F., Moscato, F.: Pattern-based orchestration and automatic verification of composite cloud services. Comput. Electr. Eng. 56, 842–853 (2016)
Amato, F., Moscato, F.: A model driven approach to data privacy verification in e-health systems. Trans. Data Priv. 8(3), 273–296 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Cuomo, S., Maiorano, F., Piccialli, F. (2019). Remarks of Social Data Mining Applications in the Internet of Data. In: Barolli, L., Kryvinska, N., Enokido, T., Takizawa, M. (eds) Advances in Network-Based Information Systems. NBiS 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-98530-5_86
Download citation
DOI: https://doi.org/10.1007/978-3-319-98530-5_86
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-98529-9
Online ISBN: 978-3-319-98530-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)