Skip to main content
SpringerLink
Log in

Dynamic Voting Interface in Social Media: Does it Affect Individual Votes?

  • Conference paper
SOFSEM 2013: Theory and Practice of Computer Science (SOFSEM 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7741))

Abstract

The rise in popularity of social media along with new web technologies has presented designers and developers with tremendous new interface opportunities for evaluating user-generated content. One of these new interface designs found in social media today, is the dynamic voting interface; voting results are public from the initiation of an evaluation procedure and are constantly being updated. However, it is currently unclear on whether these interfaces affect the outcome of a voting process and to what degree. This study employed a mixed methods survey as an attempt to try and answer these questions and provide exploratory evidence for the effects of dynamic voting interfaces on social media communities. Findings coming from this study are able to provide support for the “no effect” hypothesis.

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

Access this chapter

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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Gavish, B., Gerdes, J.H.: Voting mechanisms and their implications in a GDSS environment. Annals of Operations Research 71, 41–74 (1997)

    Article  MATH  Google Scholar 

  2. Turoff, M., Hiltz, S.R., Cho, H., Li, Z., Wang, Y.: Social Decision Support Systems (SDSS). In: Proceedings of the 35th Hawaii International Conference on System Sciences, pp. 1–10 (2002)

    Google Scholar 

  3. Hiltz, S.R., Turoff, M.: Structuring computer-mediated communication systems to avoid information overload. Communications of the ACM 28, 680–689 (1985)

    Article  Google Scholar 

  4. Gerlitz, C., Helmond, A.: Hit, Link, Like and Share. Organizing the social and the fabric of the web in a Like economy. In: DMI Mini Conference University of Amsterdam, pp. 24–25 (2011)

    Google Scholar 

  5. Li, Z.: Design and evaluation of a voting tool in a collaborative environment (2003)

    Google Scholar 

  6. Wagenmakers, E.-J., Lee, M.D., Lodewyckx, T., Iverson, G.: Bayesian versus frequentist inference. In: Hoijtink, H., Klugkist, I., Boelen, P.A. (eds.) Bayesian Evaluation of Informative Hypotheses in Psychology, pp. 181–207. Springer, New York (2008)

    Chapter  Google Scholar 

  7. Kaptein, M., Robertson, J.: Rethinking statistical analysis methods for CHI. In: Proceedings of the 2012 ACM Annual Conference on Human Factors in Computing Systems, CHI 2012, p. 1105 (2012)

    Google Scholar 

  8. Bryman, A.: Social Research Methods. Oxford University Press, Oxford (2012)

    Google Scholar 

  9. Kaplan, A.M., Haenlein, M.: Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons 53, 59–68 (2010)

    Article  Google Scholar 

  10. Kaplan, A.M., Haenlein, M.: The early bird catches the news: Nine things you should know about micro-blogging. Business Horizons 54, 105–113 (2011)

    Article  Google Scholar 

  11. Dennis, A.R., George, J.F., Jessup, L.M., Nunamaker, J.F., Vogel, D.R.: Information technology to support electronic meetings. MIS Quarterly 12, 591–624 (1988)

    Article  Google Scholar 

  12. Dufner, D., Hiltz, S.R., Turoff, M.: Distributed group support: a preliminary analysis of the effects of the use of voting tools and sequential procedures. In: Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences. Information Systems: Collaboration Technology Organizational Systems and Technology, vol. IV, pp. 114–123. IEEE (1994)

    Google Scholar 

  13. Fjermestad, J.: An Integrated Framework for Group Support Systems. Journal of Organizational Computing and Electronic Commerce 8, 83–107 (1998)

    Article  Google Scholar 

  14. Ki Jeong, C., Hung Kook, P.: Examining the conflicting results of GDSS research. Information Management 33, 313–325 (1998)

    Article  Google Scholar 

  15. Li, Z., Cheng, K.-E., Wang, Y., Hiltz, S.R.: Thurstone’s Law of Comparative Judgment for Group Support. In: AMCIS 2001 Proceedings, Paper 48 (2001)

    Google Scholar 

  16. Pervan, G.P., Atkinson, D.J.: GDSS research: An overview and historical analysis. Group Decision and Negotiation 4, 475–483 (1995)

    Article  Google Scholar 

  17. Seibold, D.R., Heller, M.A., Contractor, N.S.: Group decision support systems (GDSS): Review, taxonomy, and research agenda. In: Kovačič, B. (ed.) New Approaches to Organizational Communication, pp. 143–168. SUNY Press (1994)

    Google Scholar 

  18. Nunamaker, J.F., Dennis, A.R., Valacich, J.S., Vogel, D., George, J.F.: Electronic meeting systems. Communications of the ACM 34, 40–61 (1991)

    Article  Google Scholar 

  19. Turoff, M., Hiltz, S.R., Bahgat, A.N.F., Rana, A.R.: Distributed Group Support Systems. MIS Quarterly 17, 399–417 (1993)

    Article  Google Scholar 

  20. Dummett, M.A.E.: Voting Procedures. Clarendon Press (1984)

    Google Scholar 

  21. Felsenthal, D.S.: Topics in social choice: sophisticated voting, efficacy, and proportional representation. Praeger (1990)

    Google Scholar 

  22. Brams, S.J.: Alternative Voting Systems. In: Maisel, L.S. (ed.) Political Pareties and Elections in the United States: An Encyclopedia, pp. 23–31. Garland, New York (1991)

    Google Scholar 

  23. Hiltz, S.R., Turoff, M., Johnson, K.: Experiments in group decision making, 3: disinhibition, deindividuation, and group process in pen name and real name computer conferences. Decision Support Systems 5, 217–232 (1989)

    Article  Google Scholar 

  24. Hoffman, L.J.: Internet voting: will it spur or corrupt democracy? In: Proceedings of the Tenth Conference on Computers, Freedom and Privacy: Challenging the Assumptions, pp. 219–223. ACM, New York (2000)

    Chapter  Google Scholar 

  25. Ladner, A., Pianzola, J.: Do Voting Advice Applications Have an Effect on Electoral Participation and Voter Turnout? Evidence from the 2007 Swiss Federal Elections. In: Tambouris, E., Macintosh, A., Glassey, O. (eds.) ePart 2010. LNCS, vol. 6229, pp. 211–224. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  26. Heymann, P., Koutrika, G., Garcia-Molina, H.: Can social bookmarking improve web search? In: Proceedings of the International Conference on Web Search and Web Data Mining, WSDM 2008, vol. 301, p. 195 (2008)

    Google Scholar 

  27. Turnbull, D.: Rating, voting & ranking: designing for collaboration & consensus. In: CHI 2007 Extended Abstracts on Human Factors in Computing Systems, pp. 2705–2710 (2007)

    Google Scholar 

  28. Youtube: Statistics, http://www.youtube.com/static?template=pressstatistics

  29. Zhang, L., Tu, W.: Six Degrees of Separation in Online Society. Distribution 3, 1–5 (2006)

    Google Scholar 

  30. Wright, J.D., Marsden, P.V.: Survey Research and Social Science: History, Current Practice, and Future Prospects. In: Wright, J.D., Marsden, P.V. (eds.) Handbook of Survey Research, pp. 3–26. Emerald Group Publishing, Bingley (2010)

    Google Scholar 

  31. Lewin, C.: Understanding and Describing Quantitative Data. In: Somekh, B., Lewin, C. (eds.) Research Methods in the Social Sciences, pp. 220–230. Sage, London (2005)

    Google Scholar 

  32. Tsikerdekis, M.: The choice of complete anonymity versus pseudonymity for aggression online. eMinds International Journal on Human-Computer Interaction 2, 35–57 (2012)

    Google Scholar 

  33. Watts, D.J., Dodds, P.S., Newman, M.E.J.: Identity and Search in Social Networks. Science 296, 1302–1305 (2002)

    Article  Google Scholar 

  34. Jackman, S.: Bayesian Analysis for the Social Sciences. Wiley, Hoboken (2009)

    Book  Google Scholar 

  35. Jeffreys, H.: Theory of Probability. Clarendon Press (1998)

    Google Scholar 

  36. Kruschke, J.K.: Doing Bayesian Data Analysis: A Tutorial with R and BUGS. Academic Press (2010)

    Google Scholar 

  37. Cox, R.T.: The Algebra of Probable Inference. American Journal of Physics 31, 66 (1963)

    Article  Google Scholar 

  38. Jaynes, E.T.: Bayesian methods: general background. In: Justice, J.H. (ed.) Maximum Entropy and Bayesian Methods in Applied Statistics, pp. 1–25. Cambridge University Press (1986)

    Google Scholar 

  39. Good, I.J.: Weight of Evidence: A Brief Survey. In: Bernardo, J.M., DeGroot, M.H., Lindley, D.V., Smith, A.F.M. (eds.) Bayesian Statistics, pp. 249–269. Elsevier, New York (1985)

    Google Scholar 

  40. Lee, M.D., Wagenmakers, E.-J.: A Course in Bayesian Graphical Modeling for Cognitive Science. Convergence 7 (2010)

    Google Scholar 

  41. Albert, J.: Bayesian Computation with R. Springer, New York (2009)

    Book  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Informatics, Masaryk University, Brno, Czech Republic

    Michail Tsikerdekis

Authors
  1. Michail Tsikerdekis
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, University of Amsterdam, Plantage Muidergracht 24, 1018 TV, Amsterdam, The Netherlands

    Peter van Emde Boas

  2. Informatics Institute, Intelligent Systems Lab Amsterdam, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands

    Frans C. A. Groen

  3. Department of Civil Engineering and Computer Science, University of Rome Tor Vergata, Via del Politecnico 1, 00133, Rome, Italy

    Giuseppe F. Italiano

  4. Institute of Computing Science, Poznan University of Technology, ul. Piotrowo 2, 60-965, Poznan, Poland

    Jerzy Nawrocki

  5. Hasso-Plattner-Institute for Software Systems Engineering, Prof.-Dr.-Helmert-Str. 2-3, 14482, Potsdam, Germany

    Harald Sack

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Tsikerdekis, M. (2013). Dynamic Voting Interface in Social Media: Does it Affect Individual Votes?. In: van Emde Boas, P., Groen, F.C.A., Italiano, G.F., Nawrocki, J., Sack, H. (eds) SOFSEM 2013: Theory and Practice of Computer Science. SOFSEM 2013. Lecture Notes in Computer Science, vol 7741. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35843-2_47

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-35843-2_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35842-5

  • Online ISBN: 978-3-642-35843-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation