Online Social Networks

  • Panagiotis Symeonidis
  • Dimitrios Ntempos
  • Yannis Manolopoulos
Chapter
Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Abstract

This chapter provides: (1) some definitions and basic concepts for Online Social Networks (OSNs), (2) a brief literature review of OSNs, (3) some paradigms of commercial OSNs, and (4) the transition of OSNs towards location as an auxiliary dimension. Finally, the social and economic report of commercial OSNs helps the reader to realize the huge potential that Location-based Social Networks (LBSNs) have, based on the fact that OSNs have incorporated the location dimension in recent years.

References

  1. 1.
    L. Adamic, E. Adar, How to search a social network. Soc. Netw. 27(3), 187–203 (2005)CrossRefGoogle Scholar
  2. 2.
    D. Boyd, N. Ellison, Social network sites: definition, history, and scholarship. J. Comput. Mediat. Commun. 13(1), 210–230 (2007)CrossRefGoogle Scholar
  3. 3.
    J. Chen, W. Geyer, C. Dugan, M. Muller, I. Guy, Make new friends, but keep the old: recommending people on social networking sites, in Proceedings of the 27th International Conference on Human Factors in Computing Systems (CHI), Boston, MA (2009), pp. 201–210Google Scholar
  4. 4.
    M. Evans, A. Jamal, G. Foxall, Consumer Behaviour (Wiley, London, 2006)Google Scholar
  5. 5.
    L. Garton, C. Haythornthwaite, B. Wellman, Studying online social networks. J. Comput. Mediat. Commun. 3(1), 75–105 (1997)Google Scholar
  6. 6.
    J. Golbeck, Personalizing applications through integration of inferred trust values in semantic web-based social networks, in Proceedings of the ISWC Semantic Network Analysis Workshop (2005)Google Scholar
  7. 7.
    I. Guy, I. Ronen, E. Wilcox, Do you know?: recommending people to invite into your social network, in Proceedings of the 13th International Conference on Intelligent User Interfaces (IUI), Sanibel Island, FL (2009), pp. 77–86Google Scholar
  8. 8.
    M. Jamali, M. Ester, A matrix factorization technique with trust propagation for recommendation in social networks, in Proceedings of the 4th ACM Conference on Recommender systems(RecSys), Barcelona (2010), pp. 135–142Google Scholar
  9. 9.
    L. Katz, A new status index derived from sociometric analysis. Psychometrika 18(1), 39–43 (1953)CrossRefMATHGoogle Scholar
  10. 10.
    D. Liben-Nowell, J. Kleinberg, The link prediction problem for social networks, in Proceedings of the 12th International Conference on Information and Knowledge Management (CIKM), New Orleans, LO (2003), pp. 556–559Google Scholar
  11. 11.
    Z. Lu, B. Savas, W. Tang, I. Dhillon, Supervised link prediction using multiple sources, in Proceedings of the 10th IEEE International Conference on Data Mining (ICDM), Sydney (2010), pp. 923–928Google Scholar
  12. 12.
    P. Massa, P. Avesani, Trust-aware collaborative filtering for recommender systems, in Proceedings of Federated International Conference on the Move to Meaningful Internet (OTM): CoopIS, DOA, ODBASE, Agia Napa (2004), pp. 492–508Google Scholar
  13. 13.
    S. Milgram, The small world problem. Psychol. Today 61, 60–67 (1967)Google Scholar
  14. 14.
    J. Pan, H. Yang, C. Faloutsos, P. Duygulu, Automatic multimedia cross-modal correlation discovery, in Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Seattle, WA (2004), pp. 653–658Google Scholar
  15. 15.
    A. Papadimitriou, P. Symeonidis, Y. Manolopoulos, Fast and accurate link prediction in social networking systems. J. Syst. Softw. 85(9), 2119–2132 (2012)CrossRefGoogle Scholar
  16. 16.
    Radicati Team, Social media market, 2012–2016. Technical Report, Radicati (2012)Google Scholar
  17. 17.
    P. Symeonidis, E. Tiakas, Y. Manolopoulos, Product recommendation and rating prediction based on multi-modal social networks, in Proceedings of the 5th ACM Conference in Recommender Systems (RecSys), Chicago, IL (2011), pp. 61–68Google Scholar
  18. 18.
    P. Symeonidis, E. Tiakas, Y. Manolopoulos, A unified framework for link and rating prediction in multi-modal social networks. Int. J. Soc. Netw. Min. 1(3/4) (2013)Google Scholar
  19. 19.
    V. Vasuki, N. Natarajan, Z. Lu, I.S. Dhillon, Affiliation recommendation using auxiliary networks, in Proceedings of the 4th ACM Conference on Recommender Systems (RecSys), Barcelona (2010), pp. 103–110Google Scholar
  20. 20.
    D. Watts, S. Strogatz, Collective dynamics of small-world networks. Nature 393(6684), 440–442 (1998)CrossRefGoogle Scholar

Copyright information

© The Author(s) 2014

Authors and Affiliations

  • Panagiotis Symeonidis
    • 1
  • Dimitrios Ntempos
    • 2
  • Yannis Manolopoulos
    • 3
  1. 1.Department of Informatics Data Engineering LaboratoryAristotle University of ThessalonikiStavroupoli, ThessalonikiGreece
  2. 2.Kiwe DevelopmentThessalonikiGreece
  3. 3.Department of Informatics Data Engineering LabAristotle University of ThessalonikiStavroupoli, ThessalonikiGreece

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