Skip to main content

Influence of Timeline and Named-Entity Components on User Engagement

  • Conference paper
Advances in Information Retrieval (ECIR 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7814))

Included in the following conference series:

Abstract

Nowadays, successful applications are those which contain features that captivate and engage users. Using an interactive news retrieval system as a use case, in this paper we study the effect of timeline and named-entity components on user engagement. This is in contrast with previous studies where the importance of these components were studied from a retrieval effectiveness point of view. Our experimental results show significant improvements in user engagement when named-entity and timeline components were installed. Further, we investigate if we can predict user-centred metrics through user’s interaction with the system. Results show that we can successfully learn a model that predicts all dimensions of user engagement and whether users will like the system or not. These findings might steer systems that apply a more personalised user experience, tailored to the user’s preferences.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Attfield, S., Kazai, G., Lalmas, M., Piwowarski, B.: Towards a science of user engagement (Position Paper). In: WSDM Workshop on User Modelling for Web Applications (2011)

    Google Scholar 

  2. Overbeeke, K., Djajadiningrat, T., Hummels, C., Wensveen, S., Prens, J.: Lets make things engaging. Funology, 7–17 (2005)

    Google Scholar 

  3. O’Brien, H.L., Toms, E.G.: The development and evaluation of a survey to measure user engagement. J. Am. Soc. Inf. Sci. 61(1), 50–69 (2010)

    Article  Google Scholar 

  4. Zaragoza, H., Rode, H., Mika, P., Atserias, J., Ciaramita, M., Attardi, G.: Ranking very many typed entities on wikipedia. In: CIKM, pp. 1015–1018. ACM (2007)

    Google Scholar 

  5. Demartini, G., Missen, M.M.S., Blanco, R., Zaragoza, H.: Taer: time-aware entity retrieval-exploiting the past to find relevant entities in news articles. In: CIKM, pp. 1517–1520 (2010)

    Google Scholar 

  6. Alonso, O., Gertz, M., Baeza-Yates, R.: Clustering and exploring search results using timeline constructions. In: CIKM, pp. 97–106 (2009)

    Google Scholar 

  7. Järvelin, K.: Explaining User Performance in Information Retrieval: Challenges to IR Evaluation. In: Azzopardi, L., Kazai, G., Robertson, S., Rüger, S., Shokouhi, M., Song, D., Yilmaz, E. (eds.) ICTIR 2009. LNCS, vol. 5766, pp. 289–296. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  8. Haas, K., Mika, P., Tarjan, P., Blanco, R.: Enhanced results for web search. In: SIGIR, pp. 725–734 (2011)

    Google Scholar 

  9. Joachims, T., Granka, L., Pan, B., Hembrooke, H., Gay, G.: Accurately interpreting clickthrough data as implicit feedback. In: SIGIR, pp. 154–161 (2005)

    Google Scholar 

  10. Allan, J., Gupta, R., Khandelwal, V.: Temporal summaries of new topics. In: SIGIR, pp. 10–18 (2001)

    Google Scholar 

  11. Koen, D., Bender, W.: Time frames: Temporal augmentation of the news. IBM Systems Journal 39(3.4), 597–616 (2000)

    Google Scholar 

  12. Ringel, M., Cutrell, E., Dumais, S., Horvitz, E.: Milestones in time: The value of landmarks in retrieving information from personal stores. In: Proc. Interact, vol. 2003, pp. 184–191 (2003)

    Google Scholar 

  13. Kelly, D.: Methods for evaluating interactive information retrieval systems with users. Found. Trends Inf. Retr. 3, 1–224 (2009)

    Article  Google Scholar 

  14. Blanco, R., Halpin, H., Herzig, D.M., Mika, P., Pound, J., Thompson, H.S., Duc, T.T.: Repeatable and reliable search system evaluation using crowdsourcing. In: SIGIR, pp. 923–932 (2011)

    Google Scholar 

  15. Kittur, A., Chi, E., Suh, B.: Crowdsourcing user studies with mechanical turk. In: SIGCHI, pp. 453–456 (2008)

    Google Scholar 

  16. Kazai, G.: In Search of Quality in Crowdsourcing for Search Engine Evaluation. In: Clough, P., Foley, C., Gurrin, C., Jones, G.J.F., Kraaij, W., Lee, H., Mudoch, V. (eds.) ECIR 2011. LNCS, vol. 6611, pp. 165–176. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  17. Zuccon, G., Leelanupab, T., Whiting, S., Jose, J., Azzopardi, L.: Crowdsourcing interactions-a proposal for capturing user interactions through crowdsourcing. In: CSDM at WSDM, pp. 35–38 (2011)

    Google Scholar 

  18. Guo, Q., Agichtein, E.: Towards predicting web searcher gaze position from mouse movements. In: CHI Extended Abstracts, pp. 3601–3606 (2010)

    Google Scholar 

  19. Mason, W., Suri, S.: Conducting behavioral research on Amazon’s Mechanical Turk. Behavior Research Methods, 1–23 (June 2011)

    Google Scholar 

  20. Mason, W., Watts, D.J.: Financial incentives and the ”performance of crowds”. In: HCOMP, pp. 77–85 (2009)

    Google Scholar 

  21. Moshfeghi, Y., Piwowarski, B., Jose, J.M.: Handling data sparsity in collaborative filtering using emotion and semantic based features. In: SIGIR, pp. 625–634 (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Moshfeghi, Y., Matthews, M., Blanco, R., Jose, J.M. (2013). Influence of Timeline and Named-Entity Components on User Engagement. In: Serdyukov, P., et al. Advances in Information Retrieval. ECIR 2013. Lecture Notes in Computer Science, vol 7814. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36973-5_26

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-36973-5_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36972-8

  • Online ISBN: 978-3-642-36973-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics