Skip to main content
SpringerLink
Log in
Book cover

International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction

SBP 2015: Social Computing, Behavioral-Cultural Modeling, and Prediction pp 131–140Cite as

Subjective versus Objective Questions: Perception of Question Subjectivity in Social Q&A

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9021))

Abstract

Recent research has indicated that social networking sites are being adopted as venues for online information-seeking. In order to understand questioner’s intention in social Q&A environments and to better facilitate such behaviors, we define two types of questions: subjective information-seeking questions and objective information seeking ones. To enable automatic detection on question subjectivity, we propose a predictive model that can accurately distinguish between the two classes of questions. By applying the classifier on a larger dataset, we present a comprehensive analysis to compare questions with subjective and objective orientations, in terms of their length, response speed, as well as the characteristics of their respondents. We find that the two types of questions exhibited very different characteristics. Also, we noticed that question subjectivity plays a significant role in attracting responses from strangers. Our results validate the expected benefits of differentiating questions according to their subjectivity orientations, and provide valuable insights for future design and development of tools that can assist the information seeking process under social context.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Morris, M.R., Teevan, J., Panovich, K.: What do people ask their social networks, and why?: A survey study of status message Q & A behavior. In: SIGCHI (2010)

    Google Scholar 

  2. Lampe, C., et al.: Help is on the way: patterns of responses to resource requests on facebook. In: CSCW (2014)

    Google Scholar 

  3. Liu, Z., Jansen, B.J.: Almighty twitter, what are people asking for? In: ASIS & T (2012)

    Google Scholar 

  4. Jansen, B.J., et al.: Twitter Power: Tweets as Electronic Word of Mouth. Journal of the American Society for Information Science and Technology 60(11), 2169–2188 (2009)

    Article  Google Scholar 

  5. Zhao, Z., Mei, Q.: Questions about questions: An empirical analysis of information needs on twitter. In: WWW (2013)

    Google Scholar 

  6. Harper, F.M., Moy, D., Konstan, J.A.: Facts or friends?: distinguishing informational and conversational questions in social Q & A sites. In: SIGCHI (2009)

    Google Scholar 

  7. Li, B., et al.: Exploring question subjectivity prediction in community QA. In: SIGIR (2008)

    Google Scholar 

  8. Zhou, T.C., Si, X., Chang, Y.E., King, I., Lyu, M.R.: A data-driven approach to question subjectivity identification in community question answering. In: AAAI (2012)

    Google Scholar 

  9. Chen, L., Zhang, D., Mark, L.: Understanding user intent in community question answering. In: WWW (2012)

    Google Scholar 

  10. Aikawa, N., Sakai, T., Yamana, H.: Community qa question classification: Is the asker looking for subjective answers or not. IPSJ Online Transactions 4, 160–168 (2011)

    Article  Google Scholar 

  11. Li, B., et al.: Question identification on twitter. In: CIKM (2011)

    Google Scholar 

  12. Porter, M.F.: An Algorithm for Suffix Stripping. Program: Electronic Library and Information Systems 14(3), 130–137 (1980)

    Article  Google Scholar 

  13. Toutanova, K., et al.: Feature-rich part-of-speech tagging with a cyclic dependency network. In: NAACL2013-Volume 1

    Google Scholar 

  14. Liu, Z., Jansen, B.J.: Factors influencing the response rate in social question and answering behavior. In: CSCW (2013)

    Google Scholar 

  15. Pal, A., Margatan, J., Konstan, J.: Question temporality: identification and uses. In: CSCW (2012)

    Google Scholar 

  16. Paul, S.A., Hong, L., Chi, E.H.: Is twitter a good place for asking questions? a characterization study. In: ICWSM (2011)

    Google Scholar 

  17. Zhang, P.: Information seeking through microblog questions: The impact of social capital and relationships. In: ASIS & T (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Information Sciences and Technology, The Pennsylvania State University, University Park, PA, 16802, USA

    Zhe Liu & Bernard J. Jansen

Authors
  1. Zhe Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bernard J. Jansen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhe Liu .

Editor information

Editors and Affiliations

  1. University of Arkansas, Little Rock, Arkansas, USA

    Nitin Agarwal

  2. Technicolor Research, Los Altos, California, USA

    Kevin Xu

  3. University of Saskatchewan, Saskatoon, Saskatchewan, Canada

    Nathaniel Osgood

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Liu, Z., Jansen, B.J. (2015). Subjective versus Objective Questions: Perception of Question Subjectivity in Social Q&A. In: Agarwal, N., Xu, K., Osgood, N. (eds) Social Computing, Behavioral-Cultural Modeling, and Prediction. SBP 2015. Lecture Notes in Computer Science(), vol 9021. Springer, Cham. https://doi.org/10.1007/978-3-319-16268-3_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-16268-3_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16267-6

  • Online ISBN: 978-3-319-16268-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation