Advertisement

Abstract

A closer look at how users perform search is needed in order to best design a more efficient next generation sentiment search engine and understand fundamental behaviours involved in online review/opinion search processes. The paper proposes utilizing personalized search, eye tracking and sentiment analysis for better understanding of end-user behavioural characteristics while making a judgement in a Sentiment Search Engine.

Keywords

Sentiment Analysis Sentiment Search Eye Tracking 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Sherman, C.: Why search engines fail. Search Engine Watch (August 29, 2002)Google Scholar
  2. 2.
  3. 3.
    Nordlie, R.: User revealment – a comparison of initial queries and ensuing question development in online searching and human reference interaction. In: Proceedings of SIGIR, New York, USA, pp. 11–18 (1999)Google Scholar
  4. 4.
    Schwartz, B.: The paradox of choice – why more is less. Google Tech Talks (2006), http://www.youtube.com/watch?v=6ELAkV2fC-I
  5. 5.
    Winter, S., Tomko, M.: Translating the web semantics of georeferences. In: Web Semantics and Ontology, pp. 297–333. Idea Publishing (2006)Google Scholar
  6. 6.
    Koutrika, G., Ioannidis, Y.: A unified user-profile framework for query disambiguation and personalization. In: Proceedings of the Workshop on New Technologies for Personalized Information Access, Edinburgh, UK, pp. 44–53 (2005)Google Scholar
  7. 7.
    Granka, L., Joachims, T., Gay, G.: Eye-tracking analysis of user behavior in WWW search. In: Proceedings of the SIGIR Conference on Research and Development in Information Retrieval, New York, USA, pp. 478–479 (2004)Google Scholar
  8. 8.
    Lorigo, L., Pan, B., Hembrooke, H., Joachims, T., Granka, L., Gay, G.: The influence of task and gender on search and evaluation behavior using Google. Information Processing and Management 42(4), 1123–1131 (2006)CrossRefGoogle Scholar
  9. 9.
    Glaholt, M.G., Wu, M.-C., Reingold, E.M.: Predicting preference from fixations. PsychNology Journal 7(2), 141–158 (2009)Google Scholar
  10. 10.
    Rayner, K., Miller, B., Rotello, C.M.: Eye movements when looking at print advertisements: the goal of the viewer matters. Appplied Cognitive Psychology 22, 697–707 (2008)CrossRefGoogle Scholar
  11. 11.
    Glaholt, M.G., Reingold, E.M.: Eye movement monitoring as a process tracing methodology in decision making research. Journal of Neuroscience, Psychology, and Economics 4(2), 125–146 (2011)CrossRefGoogle Scholar
  12. 12.
    Kosinski, M., Stillwell, D., Kohli, P., Bachrach, Y., Graepel, T.: Personality and Website Choice. In: Proceedings of WebSci 2012, Evanston, Illinois, USA (2012)Google Scholar
  13. 13.
    Pradeep, A., Knight, R.T., Gurumoorthy, R.: Neurological sentiment tracking system. United States Patent Application Publication, US 2011/0270620 A1 (November 3, 2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Amitava Das
    • 1
  • Björn Gambäck
    • 2
  1. 1.SAIT Lab.Samsung Research IndiaBangaloreIndia
  2. 2.Norwegian University of Science and TechnologyTrondheimNorway

Personalised recommendations