TrustVis: A Trust Visualisation Service for Online Communities

  • Sanat Kumar Bista
  • Payam Aghaei Pour
  • Nathalie Colineau
  • Surya Nepal
  • Cecile Paris
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7759)


Visualisation of social behaviour of members in online communities is a challenging issue. It provides holistic information on the behaviour of the community to the administrators/moderators and helps individual members in the community to monitor and analyse their own behaviour. This paper presents the design and implementation of a social trust visualisation service, called TrustVis, where the social trust is derived from the social behaviour of members in the community. One of the unique features of TrustVis is that it supports the faceted browsing and monitoring of members’ social behaviour based on activities, contexts, time and roles. TrustVis is implemented and deployed in an online community we are currently trialling in collaboration with a government department to deliver support services to welfare recipients during their transition back to work. We describe the look and feel and the working of TrustVis in our production environment.


Social Network Social Network Analysis Visualisation Tool Online Social Network Social Trust 
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.
    Rheingold, H.: The Virtual Community: Homesteading on the Electronic Frontier (Revised Edition). MIT Press, USA (2000)Google Scholar
  2. 2.
    Ellison, N.B., Steinfield, C., Lampe, C.: The Benefits of Facebook “Friends:” Social Capital and College Students’ Use of Online Social Network Sites. Journal of Computer-Mediated Communication 12(4), 1143–1168 (2007), doi:10.1111/j.1083-6101.2007.00367.xCrossRefGoogle Scholar
  3. 3.
    Colineau, N., Paris, C., Dennett, A.: Exploring the Use of an Online Community in Welfare Transition Programs. In: 25th BCS Conference on Human-Computer Interaction, Newcastle-upon-Tyne, United Kingdom, pp. 455–460. British Computer Society (2011)Google Scholar
  4. 4.
    Colineau, N., Paris, C., Dennett, A.: Capitalising on the Potential of Online Communities to Help Welfare Recipients. International Reports on Socio-Informatics (IRSI) 2, 59–65 (2011)Google Scholar
  5. 5.
    Dekker, A.: Visualisation of social networks using CAVALIER. In: Proceedings of the 2001 Asia-Pacific Symposium on Information Visualisation, Sydney, Australia, vol. 9, pp. 49–55. Australian Computer Society, Inc. (2001)Google Scholar
  6. 6.
    Freeman, L.C.: Visualizing Social Networks. Journal of Social Structure 1(1) (2000)Google Scholar
  7. 7.
    Heer, J., Boyd, D.: Vizster: visualizing online social networks. In: IEEE Symposium on Information Visualization, INFOVIS 2005, USA, October 23-25, pp. 32–39 (2005), doi:10.1109/infvis.2005.1532126Google Scholar
  8. 8.
    Jyothi, S., McAvinia, C., Keating, J.: A visualisation tool to aid exploration of students’ interactions in asynchronous online communication. Computers & Education 58(1), 30–42 (2012), doi:10.1016/j.compedu.2011.08.026CrossRefGoogle Scholar
  9. 9.
    Girardin, L.: An eye on network intruder-administrator shootouts. In: Proceedings of the 1st Workshop on Intrusion Detection and Network Monitoring, Santa Clara, California, vol. 1. USENIX Association (1999)Google Scholar
  10. 10.
    Ball, R., Fink, G.A., North, C.: Home-centric visualization of network traffic for security administration. In: Proceedings of the 2004 ACM Workshop on Visualization and Data Mining for Computer Security, Washington DC, USA, pp. 55–64. ACM (2004), doi:10.1145/1029208.1029217Google Scholar
  11. 11.
    Erbacher, R.F.: Intrusion behavior detection through visualization. In: IEEE Systems, Man and Cybernetics Conference, Cristal City, Virginia, USA, October 5-8, pp. 2507–2513. IEEE (2003), doi:10.1109/icsmc.2003.1244260Google Scholar
  12. 12.
    de Nooy, W., Mrvar, A., Batagelj, V.: Exploratory Social Network Analysis with Pajek. Cambridge University Press, USA (2011)CrossRefGoogle Scholar
  13. 13.
    Borgatti, S.P.: Ucinet for Windows: Software for Social Network Analysis. Analytic Technologies, Harvard (2002)Google Scholar
  14. 14.
    Opsahl, T.: Structure and Evolution of Weighted Networks. University of London (Queen Mary College), London (2009)Google Scholar
  15. 15.
    Iba, T., Nemoto, K., Peters, B., Gloor, P.A.: Analyzing the Creative Editing Behavior of Wikipedia Editors: Through Dynamic Social Network Analysis. Procedings of Social and Behavioral Sciences 2(4), 6441–6456 (2010), doi:10.1016/j.sbspro.2010.04.054CrossRefGoogle Scholar
  16. 16.
    Nepal, S., Sherchan, W., Paris, C.: Building Trust Communities Using Social Trust. In: Ardissono, L., Kuflik, T. (eds.) UMAP 2011 Workshops. LNCS, vol. 7138, pp. 243–255. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  17. 17.
    Nepal, S., Paris, C., Bista, S.K., Sherchan, W.: A Trust Model Based Analysis of Social Networks. International Journal of Trust Management in Computing and Communications (2012) (forthcoming) Google Scholar
  18. 18.
    Henry, N., Fekete, J.D., McGuffin, M.J.: NodeTrix: a Hybrid Visualization of Social Networks. IEEE Transactions on Visualization and Computer Graphics 13(6), 1302–1309 (2007), doi:10.1109/tvcg.2007.70582CrossRefGoogle Scholar
  19. 19.
    Henry, N., Fekete, J.D.: MatrixExplorer: a Dual-Representation System to Explore Social Networks. IEEE Transactions on Visualization and Computer Graphics 12(5), 677–684 (2006), doi:10.1109/tvcg.2006.160CrossRefGoogle Scholar
  20. 20.
    Scott, J.: Social Network Analysis: A Handbook. Sage Publications, London (1987)Google Scholar
  21. 21.
    Xiong, R., Donath, J.: PeopleGarden: creating data portraits for users. In: Proceedings of the 12th Annual ACM Symposium on User Interface Software and Technology, Asheville, North Carolina, USA, pp. 37–44. ACM (1999), doi:10.1145/320719.322581Google Scholar
  22. 22.
    Viégas, F.B., Donath, J.: Social network visualization: can we go beyond the graph. In: Workshop on Social Networks for Design and Analysis: Using Network Information, Chicago, USA (2004)Google Scholar
  23. 23.
    O’Donovan, J.: Capturing Trust in Social Web Applications Computing with Social Trust. In: Golbeck, J. (ed.) Human–Computer Interaction Series, pp. 213–257. Springer, London (2009), doi:10.1007/978-1-84800-356-9_9Google Scholar
  24. 24.
    O’Donovan, J., Smyth, B., Evrim, V., McLeod, D.: Extracting and visualizing trust relationships from online auction feedback comments. In: Proceedings of the 20th International Joint Conference on Artifical Intelligence, Hyderabad, India, pp. 2826–2831. Morgan Kaufmann Publishers Inc. (2007)Google Scholar
  25. 25.
    Guerriero, A., Kubicki, S., Halin, G.: Trust-Oriented Multi-visualization of Cooperation Context. In: Proceedings of the Second International Conference in Visualisation, pp. 96–101. IEEE Computer Society, Washington, DC (2009), doi:10.1109/viz.2009.48Google Scholar
  26. 26.
    Bimrah, K.K., Mouratidis, H., Preston, D.: Modelling Trust Requirements by Means of a Visualization Language. In: Proceedings of the 2008 Requirements Engineering Visualization, Barcelona, Spain, pp. 26–30. IEEE Computer Society (2008), doi:10.1109/rev.2008.3Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Sanat Kumar Bista
    • 1
  • Payam Aghaei Pour
    • 1
  • Nathalie Colineau
    • 1
  • Surya Nepal
    • 1
  • Cecile Paris
    • 1
  1. 1.Information Engineering LaboratoryCSIRO ICT CentreAustralia

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