COBRA – A Visualization Solution to Monitor and Analyze Consumer Generated Medias

  • Amit Behal
  • Julia Grace
  • Linda Kato
  • Ying Chen
  • Shixia Liu
  • Weijia Cai
  • Weihong Qian
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5618)

Abstract

Consumer Generated Medias (CGMs) – such as blogs, news forums, message boards, and web pages – are emerging as locations where consumers trade, discuss and influence each other’s purchasing patterns. Leveraging such CGMs to provide valuable insight into consumer opinions and trends is becoming increasingly attractive to corporations. This paper describes COBRA (COrporate Brand and Reputation Analysis), a visual analytics solution that surfaces the text mining and statistical analysis capabilities described in our earlier COBRA papers. Our interaction technique of search, visualization, and monitor enables detailed analysis of many CGMs without overwhelming the user. A suite of visualization solutions expose a variety of embedded COBRA visual analytics capabilities. Real world client engagements and user studies demonstrate the effectiveness of our approach.

Keywords

visual analytics text mining semi structured search 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Spangler, S., Chen, Y., Proctor, L., Lelescu, A., Behal, A., He, B., Griffin, T.D., Liu, A., Wade, B., Davis, T.: COBRA - Mining Web for Corporate Brand and Reputation Analysis. In: IEEE/WIC/ACM, International Conference on Web Intelligence, pp. 11–17 (2007)Google Scholar
  2. 2.
    Kieliszewski, C., Cui, J., Behal, A., Lelescu, A., Hubbard, T.: A Visualization Solution for the Analysis and Identification of Workforce Expertise. In: Smith, M.J., Salvendy, G. (eds.) HCII 2007. LNCS, vol. 4557, pp. 317–326. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  3. 3.
    Behal, A., Chen, Y., Kieliszewski, Y., Lelescu, A., He, B., Cui, J., Kreulen, J., Rhodes, J., Spangler, S.: Business Insights Workbench – An Interactive Insights Discovery Solution. In: Human Interface and the Management of Information. Interacting in Information Environments, pp. 834–843. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  4. 4.
    Spangler, S., Kreulen, J.: Interactive methods for taxonomy editing and validation. In: ACM CIKM (2002)Google Scholar
  5. 5.
    Ghoniem, M., Fekete, J.D., Castagliola, P.: On the readability of graphs using node-link and matrix-based representations: a controlled experiment and statistical analysis. Information Visualization 4(2), 114–135 (2005)Google Scholar
  6. 6.
    Cai, K., Spangler, S., Chen, Y., Zhang, L.: Leveraging Sentiment Analysis for Topic Detection. In: 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, pp. 265–271 (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Amit Behal
    • 1
  • Julia Grace
    • 1
  • Linda Kato
    • 1
  • Ying Chen
    • 1
  • Shixia Liu
    • 2
  • Weijia Cai
    • 2
  • Weihong Qian
    • 2
  1. 1.IBM Almaden Research CenterSan JoseUSA
  2. 2.IBM China Research LabPeople's Republic of China

Personalised recommendations