On Wires and Cables: Content Analysis of WikiLeaks Using Self-Organising Maps

  • Rudolf Mayer
  • Andreas Rauber
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6731)


The Self-Organising Map has been frequently employed to organise collections of digital documents, especially textual documents. SOMs can be employed to analyse the content and relations between the documents in a collection, providing an intuitive access to large collections.

In this paper, we apply this approach to analysing documents from the Internet platform WikiLeaks. This document collection is interesting for such an analysis for several aspects. For one, the documents contained cover a rather large time-span, thus there should also be an quite divergence in the topics discussed. Further, the documents stem from a magnitude of different sources, thus different styles should be expected. Moreover, the documents have very interesting, previously unpublished content. Finally, while the WikiLeaks website provides a way to browse all documents published by certain meta-data categories such as creation year and origin of the cable, there is no way to access the documents by their content. Thus, the SOM offers a valuable alternative mean to provide access to the content of the collection by their content.

For analysing the document collection, we employ the Java SOMToolbox framework, which provides the user with a wealth of analysis and interaction methods, such as different visualisations, zooming and panning, and automatic labelling on different levels of granularity, to help the user in quickly getting an overview of and navigating in the collection.


International Atomic Energy Agency Voronoi Diagram Document Collection Voronoi Cell Model Vector 
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.


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  1. 1.
    Dittenbach, M., Rauber, A., Merkl, D.: Business, Culture, Politics, and Sports - How to Find Your Way through a Bulk of News? In: Mayr, H.C., Lazanský, J., Quirchmayr, G., Vogel, P. (eds.) DEXA 2001. LNCS, vol. 2113, pp. 200–220. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  2. 2.
    Ward Jr., J.H.: Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association 58(301), 236–244 (1963)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Kohonen, T., Kaski, S., Lagus, K., Salojärvi, J., Paatero, V., Saarela, A.: Organization of a massive document collection. IEEE Transactions on Neural Networks, Special Issue on Neural Networks for Data Mining and Knowledge Discovery 11(3), 574–585 (2000)CrossRefGoogle Scholar
  4. 4.
    Mayer, R., Aziz, T.A., Rauber, A.: Visualising Class Distribution on Self-organising Maps. In: de Sá, J.M., Alexandre, L.A., Duch, W., Mandic, D.P. (eds.) ICANN 2007. LNCS, vol. 4669, pp. 359–368. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  5. 5.
    Pampalk, E., Rauber, A., Merkl, D.: Using Smoothed Data Histograms for Cluster Visualization in Self-Organizing Maps. In: Dorronsoro, J.R. (ed.) ICANN 2002. LNCS, vol. 2415, pp. 871–876. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  6. 6.
    Pölzlbauer, G., Dittenbach, M., Rauber, A.: Advanced visualization of self-organizing maps with vector fields. Neural Networks 19(6–7), 911–922 (2006)CrossRefzbMATHGoogle Scholar
  7. 7.
    Rauber, A., Merkl, D.: Automatic labeling of Self-Organizing Maps for Information Retrieval. Journal of Systems Research and Inf. Systems (JSRIS) 10(10), 23–45 (2001)Google Scholar
  8. 8.
    Salton, G.: Automatic text processing – The Transformation, Analysis, and Retrieval of Information by Computer. Addison-Wesley Longman Publishing Co., Inc., Amsterdam (1989)Google Scholar
  9. 9.
    Ultsch, A., Siemon, H.P.: Kohonen’s Self-Organizing Feature Maps for Exploratory Data Analysis. In: Proceedings of the International Neural Network Conference (INNC 1990), pp. 305–308. Kluwer Academic Publishers, Dordrecht (1990)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Rudolf Mayer
    • 1
  • Andreas Rauber
    • 1
  1. 1.Institute of Software Technology and Interactive SystemsVienna University of TechnologyAustria

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