Abstract
Evaluating large sets of items, such as business ideas, is a difficult task. While no one person has time to evaluate all the items, many people can contribute by each evaluating a few. Moreover, given the mobility of people, it is useful to allow them to evaluate items from their mobile devices. We present the design and implementation of a mobile service, Rankr, which provides a lightweight and efficient way to crowdsource the relative ranking of ideas, photos, or priorities through a series of pairwise comparisons. We discover that users prefer viewing two items simultaneously versus viewing one image at a time with better fidelity. Additionally, we developed an algorithm that determines the next most useful pair of candidates a user can evaluate to maximize the information gained while minimizing the number of votes required. Voters do not need to compare and manually rank all of the candidates.
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References
Arrow, K.J.: Social Choice and Individual Value. Wiley (1963)
David, H.A.: The Method of Paired Comparisons. Oxford University Press, New York (1988)
Elo, A.E.: The rating of chess players: Past and present. Arco Publishing, New York (1978)
Green, P.E., Srinivasan, V.: Conjoint analysis in marketing: New developments with implications for research and practice. The Journal of Marketing 54(4), 3–19 (1990)
Hacker, S., Ahn, L.V.: Matchin: Eliciting user preferences with an online game. In: Proc. of the SIGCHI Conf. on Human Factors in Computing Systems. ACM (2009)
Hochbaum, D.S.: The separation, and separation-deviation methodology for group decision making and aggregate ranking. In: Hasenbein, J.J. (ed.) TutORials in Operations Research, INFORMS, Hanover, MD, vol. 7, pp. 116–141 (2010)
Mas-Collel, A., Whinston, M.D., Green, J.R.: Microeconomic Theory. Oxford University Press (1995)
Sarma, A.D., Sarma, A.D., Gollapudi, S., Panigrahy, R.: Ranking mechanisms in twitter-like forums. In: Proc. Conf. on Web Search and Data Mining (2010)
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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Luon, Y., Aperjis, C., Huberman, B.A. (2012). Rankr: A Mobile System for Crowdsourcing Opinions. In: Zhang, J.Y., Wilkiewicz, J., Nahapetian, A. (eds) Mobile Computing, Applications, and Services. MobiCASE 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 95. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32320-1_2
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DOI: https://doi.org/10.1007/978-3-642-32320-1_2
Publisher Name: Springer, Berlin, Heidelberg
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