Skip to main content
SpringerLink
Log in
Book cover

International Conference on Social Informatics

SocInfo 2012: Social Informatics pp 365–378Cite as

Swayed by Friends or by the Crowd?

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7710))

Abstract

We have conducted three empirical studies of the effects of friend recommendations and general ratings on how online users make choices. We model and quantify how a user deciding between two choices trades off an additional rating star with an additional friend’s recommendation when selecting an item. We find that negative opinions from friends are more influential than positive opinions, and people exhibit “more random” behavior in their choices when the decision involves less cost and risk. Our results are quite general in the sense that people across different demographics trade off recommendations from friends and ratings from the general public in a similar fashion.

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. Iyengar, R., Van den Bulte, C., Valente, T.W.: Opinion leadership and social contagion in new product diffusion. Marketing Science 30, 195–212 (2011)

    Article  Google Scholar 

  2. Aral, S., Walker, D.: Creating social contagion through viral product design: A randomized trial of peer influence in networks. In: Proceedings of the 31th Annual International Conference on Information Systems (2010)

    Google Scholar 

  3. Lelis, S., Howes, A.: Informing decisions: how people use online rating information to make choices. In: Proceedings of the, Annual Conference on Human Factors in Computing systems, pp. 2285–2294. ACM (2011)

    Google Scholar 

  4. Luca, M.: Reviews, reputation, and revenue: The case of yelp. com. Harvard Business School Working Papers (2011)

    Google Scholar 

  5. Sorensen, A.: Social learning and health plan choice. The RAND Journal of Economics 37(4), 929–945 (2006)

    Article  Google Scholar 

  6. Glaeser, E., Sacerdote, B., Scheinkman, J.: Crime and social interactions. National Bureau of Economic Research, Cambridge (1995)

    Google Scholar 

  7. Hullman, J., Adar, E., Shah, P.: The impact of social information on visual judgments. In: Proceedings of the 2011 Annual Conference on Human Factors in Computing Systems, pp. 1461–1470. ACM (2011)

    Google Scholar 

  8. Al-Hasan, A., Viswanathan, S.: The new roi return on influentials. Working Paper (2010)

    Google Scholar 

  9. Hong, H., Kubik, J., Stein, J.: Social interaction and stock-market participation. The Journal of Finance 59(1), 137–163 (2004)

    Article  Google Scholar 

  10. Tucker, C., Zhang, J.: How does popularity information affect choices? a field experiment. Management Science (forthcoming 2011)

    Google Scholar 

  11. Salganik, M., Dodds, P., Watts, D.: Experimental study of inequality and unpredictability in an artificial cultural market. Science 311(5762), 854 (2006)

    Article  Google Scholar 

  12. Guo, S., Wang, M., Leskovec, J.: The role of social networks in online shopping: information passing, price of trust, and consumer choice. In: ACM Conference on Electronic Commerce (2011)

    Google Scholar 

  13. Guy, I., Zwerdling, N., Carmel, D., Ronen, I., Uziel, E., Yogev, S., Ofek-Koifman, S.: Personalized recommendation of social software items based on social relations. In: RecSys, pp. 53–60 (2009)

    Google Scholar 

  14. Groh, G., Ehmig, C.: Recommendations in taste related domains: collaborative filtering vs. social filtering. In: GROUP, pp. 127–136 (2007)

    Google Scholar 

  15. Sinha, R.R., Swearingen, K.: Comparing recommendations made by online systems and friends. In: DELOS Workshop: Personalisation and Recommender Systems in Digital Libraries (2001)

    Google Scholar 

  16. Mason, W., Suri, S.: Conducting behavioral research on amazon’s mechanical turk. Behavior Research Methods, 1–23 (2010)

    Google Scholar 

  17. Kittur, A., Chi, E., Suh, B.: Crowdsourcing user studies with mechanical turk. In: Proceedings of the Twenty-Sixth Annual SIGCHI Conference on Human Factors in Computing Systems, pp. 453–456. ACM (2008)

    Google Scholar 

  18. Horton, J.J., Rand, D.G., Zeckhauser, R.: The online laboratory: Conducting experiments in a real labor market. Experimental Economics (2011)

    Google Scholar 

  19. Heer, J., Bostock, M.: Crowdsourcing graphical perception: using mechanical turk to assess visualization design. In: Proceedings of the 28th International Conference on Human Factors in Computing Systems, CHI 2010, pp. 203–212. ACM, New York (2010)

    Google Scholar 

  20. Heppner, P., Wampold, B., Kivlighan, D.: Research design in counseling. Brooks/Cole Pub. Co. (2008)

    Google Scholar 

  21. Paez, A., Scott, D., Volz, E.: A discrete-choice approach to modeling social influence on individual decision making. Environment and Planning B: Planning and Design 35(6), 1055–1069 (2008)

    Article  Google Scholar 

  22. Hardin, J., Hilbe, J., Hilbe, J.: Generalized linear models and extensions. Stata Corp. (2007)

    Google Scholar 

  23. Baumeister, R., Bratslavsky, E., Finkenauer, C., Vohs, K.: Bad is stronger than good. Review of General Psychology 5(4), 323 (2001)

    Article  Google Scholar 

  24. Peeters, G., Czapinski, J.: Positive-negative asymmetry in evaluations: The distinction between affective and informational negativity effects. European Review of Social Psychology 1, 33–60 (1990)

    Article  Google Scholar 

  25. Taylor, S.: Asymmetrical effects of positive and negative events: The mobilization-minimization hypothesis. Psychological Bulletin 110(1), 67 (1991)

    Article  Google Scholar 

  26. Cheung, C., Lee, M.: Online consumer reviews: Does negative electronic word-of-mouth hurt more? In: AMCIS 2008 Proceedings, p. 143 (2008)

    Google Scholar 

  27. Hao, Y., Ye, Q., Li, Y., Cheng, Z.: How does the valence of online consumer reviews matter in consumer decision making? differences between search goods and experience goods. In: 2010 43rd Hawaii International Conference on System Sciences (HICSS), pp. 1–10. IEEE (2010)

    Google Scholar 

  28. Anderson, N.: Averaging versus adding as a stimulus-combination rule in impression formation. Journal of Experimental Psychology 70(4), 394 (1965)

    Article  Google Scholar 

  29. Anderson: Foundations of Information Integration Theory. Academic Press, New York (1981)

    Google Scholar 

  30. Kahneman, D., Tversky, A.: Prospect theory: An analysis of decision under risk. Econometrica: Journal of the Econometric Society, 263–291 (1979)

    Google Scholar 

  31. Golbeck, J., Hendler, J.: Filmtrust: Movie recommendations using trust in web-based social networks. In: Proceedings of the IEEE Consumer Communications and Networking Conference, vol. 96. Citeseer (2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, Columbia University, New York, NY, USA

    Zeinab Abbassi

  2. Social Computing Group, HP Labs, Palo Alto, CA, USA

    Christina Aperjis & Bernardo A. Huberman

Authors
  1. Zeinab Abbassi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christina Aperjis
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bernardo A. Huberman
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Distributed Information Systems Laboratory (LSIR), School for Computer and Communication Science (I&C), EPFL-IC,, Bâtiment BC, Station 14, 1015, Lausanne, Switzerland

    Karl Aberer

  2. Department of Sociology, ICS, University of Groningen, Grote Rozenstraat 31, 9712 TG, Groningen, The Netherlands

    Andreas Flache

  3. Groningen Center for Social Complexity Studies, Nettelbosje 2, 9747 AE, Groningen, The Netherlands

    Wander Jager

  4. Georgia Institute of Technology, KACB, room 3340,School of Computer Science, College of Computing, 266 Ferst Dr, 30332-0765, Atlanta, GA, USA

    Ling Liu

  5. Tsinghua University, Rm 1-308, FIT Building, 100084, Beijing, China

    Jie Tang

  6. Data Archiving and Networked Services (DANS), Anna van Saksenlaan 10, 2593 HT, Den Haag, The Netherlands

    Christophe Guéret

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Abbassi, Z., Aperjis, C., Huberman, B.A. (2012). Swayed by Friends or by the Crowd?. In: Aberer, K., Flache, A., Jager, W., Liu, L., Tang, J., Guéret, C. (eds) Social Informatics. SocInfo 2012. Lecture Notes in Computer Science, vol 7710. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35386-4_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-35386-4_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35385-7

  • Online ISBN: 978-3-642-35386-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation