Semantics, Sensors, and the Social Web: The Live Social Semantics Experiments

  • Martin Szomszor
  • Ciro Cattuto
  • Wouter Van den Broeck
  • Alain Barrat
  • Harith Alani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6089)


The Live Social Semantics is an innovative application that encourages and guides social networking between researchers at conferences and similar events. The application integrates data from the Semantic Web, online social networks, and a face-to-face contact sensing platform. It helps researchers to find like-minded and influential researchers, to identify and meet people in their community of practice, and to capture and later retrace their real-world networking activities. The application was successfully deployed at two international conferences, attracting more than 300 users in total. This paper describes the Live Social Semantics application, with a focus on how data from Web 2.0 sources can be used to automatically generate Profiles of Interest. We evaluate and discuss the results of its two deployments, assessing the accuracy of profiles generated, the willingness to link to external social networking sites, and the feedback given through user questionnaires.


Online Social Network Incoming Link Triple Store Social Networking Account Time Decay Factor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Alani, H., Szomszor, M., Cattuto, C., den Broeck, W.V., Correndo, G., Barrat, A.: Live social semantics. In: Bernstein, A., Karger, D.R., Heath, T., Feigenbaum, L., Maynard, D., Motta, E., Thirunarayan, K. (eds.) ISWC 2009. LNCS, vol. 5823, pp. 698–714. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  2. 2.
    Angeletou, S., Sabou, M., Motta, E.: Semantically enriching folksonomies with flor. In: Workshop on Collective Intelligence & the Semantic Web (CISWeb), ESWC, Tenerife, Spain (2008)Google Scholar
  3. 3.
    Barrat, A., Cattuto, C., Colizza, V., Pinton, J.-F., den Broeck, W.V., Vespignani, A.: High resolution dynamical mapping of social interactions with active RFID (2008),
  4. 4.
    Begelman, G., Keller, P., Smadja, F.: Automated tag clustering: Improving search and exploration in the tag space. In: Proc. 17th Int. World Wide Web Conf., Edinburgh, UK (2006)Google Scholar
  5. 5.
    den Broeck, W.V., Cattuto, C., Barrat, A., Szomszor, M., Correndo, G., Alani, H.: The live social semantics application: a platform for integrating face-to-face proximity with on-line social networking. In: Workshop on Communication, Collaboration and Social Networking in Pervasive Computing Environments (PerCol 2010), IEEE Int. Conf. on Pervasive Computing and Communications (PerCom), Mannheim, Germany (2010)Google Scholar
  6. 6.
    Eagle, N., Pentland (Sandy), A.: Reality mining: sensing complex social systems. Personal Ubiquitous Comput. 10(4), 255–268 (2006)CrossRefGoogle Scholar
  7. 7.
    Garcá-Silva, A., Szomszor, M., Alani, H., Corcho, O.: Preliminary results in tag disambiguation using dbpedia. In: Knowledge Capture (K-Cap 2009) - Workshop on Collective Knowledge Capturing and Representation - CKCaR 2009, CA, USA (2009)Google Scholar
  8. 8.
    Glaser, H., Millard, I., Jaffri, A.: A knowledge driven infrastructure for linked data providers. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS, vol. 5021, pp. 797–801. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  9. 9.
    Golder, S.A., Huberman, B.A.: Usage patterns of collaborative tagging systems. Journal of Information Science 32, 198–208 (2006)CrossRefGoogle Scholar
  10. 10.
    Guy, M., Tonkin, E.: Tidying up tags? D-Lib Magazine 12(1) (2006)Google Scholar
  11. 11.
    Hayes, C., Avesani, P., Veeramachaneni, S.: An analysis of the use of tags in a log recommender system. In: Int. Joint Conf. Artificial Intelligence (IJCAI), Hyderabad, India (2007)Google Scholar
  12. 12.
    Hui, P., Chaintreau, A., Scott, J., Gass, R., Crowcroft, J., Diot, C.: Pocket switched networks and human mobility in conference environments. In: WDTN 2005: Proc. 2005 ACM SIGCOMM workshop on Delay-tolerant networking. ACM, New York (2005)Google Scholar
  13. 13.
    Li, X., Guo, L., Zhao, Y.E.: Tag-based social interest discovery. In: Proc. 19th Int. World Wide Web Conf. (WWW), Beijing, China (2008)Google Scholar
  14. 14.
    Mathes, A.: Folksonomies - cooperative classification and communication through shared metadata. In: Computer Mediated Communication - LIS590CMC (December 2004)Google Scholar
  15. 15.
    Passant, A., Laublet, P.: Meaning of a tag: A collaborative approach to bridge the gap between tagging and linked data. In: Workshop on Linked Data on the Web (LDOW), Int. Word Wide Web Conference, Beijing, China (2008)Google Scholar
  16. 16.
    Scherrer, A., Borgnat, P., Fleury, E., Guillaume, J.-L., Robardet, C.: Description and simulation of dynamic mobility networks. Comput. Netw. 52(15), 2842–2858 (2008)zbMATHCrossRefGoogle Scholar
  17. 17.
    Specia, L., Motta, E.: Integrating folksonomies with the semantic web. In: Franconi, E., Kifer, M., May, W. (eds.) ESWC 2007. LNCS, vol. 4519, pp. 624–639. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  18. 18.
    Szomszor, M., Alani, H., Cantador, I., O’Hara, K., Shadbolt, N.: Semantic modelling of user interests based on cross-folksonomy analysis. In: Sheth, A.P., Staab, S., Dean, M., Paolucci, M., Maynard, D., Finin, T., Thirunarayan, K. (eds.) ISWC 2008. LNCS, vol. 5318, pp. 632–648. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  19. 19.
    Szomszor, M., Cantador, I., Alani, H.: Correlating user profiles from multiple folksonomies. In: Proc. Int. Conf. Hypertext (HT 2008), Pittsburgh, PA, USA (2008)Google Scholar
  20. 20.
    Tesconi, M., Ronzano, F., Marchetti, A., Minutoli, S.: Semantify automatically turn your tags into senses. In: Social Data on the Web, Workshop at the 7th ISWC (2008)Google Scholar
  21. 21.
    Thibodeau, P.: IBM uses RFID to track conference attendees (2007),
  22. 22.
    Wu, L., Waber, B., Aral, S., Brynjolfsson, E., Pentland, S.: Mining face-to-face interaction networks using sociometric badges: Evidence predicting productivity in it configuration. In: The 2008 Winter Conference on Business Intelligence, University of Utah (2008)Google Scholar
  23. 23.
    Yeung, C.-M.A., Gibbins, N., Shadbolt, N.: Tag meaning disambiguation through analysis of tripartite structure of folksonomies. In: 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Workshops, pp. 3–6 (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Martin Szomszor
    • 1
  • Ciro Cattuto
    • 2
  • Wouter Van den Broeck
    • 2
  • Alain Barrat
    • 2
    • 3
  • Harith Alani
    • 4
  1. 1.City eHealth Research CentreCity University LondonUK
  2. 2.Complex Networks and Systems GroupInstitute for Scientific Interchange (ISI) FoundationTurinItaly
  3. 3.Centre de Physique Théorique (CNRS UMR 6207)MarseilleFrance
  4. 4.Knowledge Media InstituteThe Open UniversityUK

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