Abstract
To explore whether and how different social activities and phenomena, network structures and incentive machanisms could influent human behavior in social networks, Prof. Kearns and his colleagues conducted a series of human participated behavior experiments [3]. Recently, we recurred one of those experiments called biased voting to verify whether and how the factors work on Chinese students. In this paper, we presented not only on the difference we found in the result, but also the design and preparation of the experiment to make some contributions to researchers who are interested in such experiments. We shared our source code and experiment data so that new experiments can be conducted quickly and easily.
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References
Kearns, M., Judd, S., Tan, J., Wortman, J.: Behavioral experiments on biased voting in networks. Proceedings of the National Academy of Sciences 106(5), 1347–1352 (2009)
Kearns, M., Tan, J.: Biased voting and the democratic primary problem. In: Papadimitriou, C., Zhang, S. (eds.) WINE 2008. LNCS, vol. 5385, pp. 639–652. Springer, Heidelberg (2008)
Kearns, M.: Experiments in social computation. Communications of the ACM 55(10), 56–67 (2012)
Chakraborty, T., Judd, S., Kearns, M., Tan, J.: A behavioral study of bargaining in social networks. In: Proceedings of the 11th ACM Conference on Electronic Commerce, pp. 243–252. ACM (2010)
Suri, S., Watts, D.J.: Cooperation and contagion in web-based, networked public goods experiments. PLoS One 6(3), e16836 (2011)
Centola, D.: The spread of behavior in an online social network experiment. Science 329(5996), 1194–1197 (2010)
Xie, J., Sreenivasan, S., Korniss, G., Zhang, W., Lim, C., Szymanski, B.K.: Social consensus through the influence of committed minorities. Physical Review E 84(1), 011130 (2011)
Cao, L.: In-depth Behavior Understanding and Use: the Behavior Informatics Approach. Information Science 180(17), 3067–3085 (2010)
Kleinberg, J.: Cascading behavior in networks: Algorithmic and economic issues. Algorithmic Game Theory 24, 613–632 (2007)
Granovetter, M.: Threshold models of collective behavior. American Journal of Sociology, 1420–1443 (1978)
Schelling, T.C.: Micromotives and Macrobehavior (1978)
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Zhao, C., Sun, G., Tian, Y. (2013). Design, Conduct and Analysis of a Biased Voting Experiment on Human Behavior. In: Cao, L., et al. Behavior and Social Computing. BSIC BSI 2013 2013. Lecture Notes in Computer Science(), vol 8178. Springer, Cham. https://doi.org/10.1007/978-3-319-04048-6_3
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DOI: https://doi.org/10.1007/978-3-319-04048-6_3
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04047-9
Online ISBN: 978-3-319-04048-6
eBook Packages: Computer ScienceComputer Science (R0)