Power analysis of voting games with abstention based on social networks

被引：0
|
作者：
Shi R.-L. [1 ]
Guo C.-X. [1 ]
Gu X. [1 ,2 ]
Li X.-P. [1 ]
机构：
[1] Business School, Sichuan University, Chengdu
[2] Chengdu Soft Creation Intellectual Industry Research Association, Chengdu
来源：
Kongzhi yu Juece/Control and Decision | 2020年 / 35卷 / 11期
关键词：
Group decision-making; Network power; Power index; Social networks; Voting games with abstention;
D O I：
10.13195/j.kzyjc.2019.0346
中图分类号：
学科分类号：
摘要：
This paper proposes a novel power index considering the dual influence of voting rules and social network effect. We analyzed the influence of the change of voter's viewpoint on voting result based on the influence network which is designed by constructing the social network of decision group and measuring the degree of influence between nodes. The ability of voters to achieve their own decision purpose by influencing others' behavior is defined as the network power, and a network power measure method is proposed by extending the power index of Banzhaf. The properties and influencing factors of the network power index, and its difference from Banzhaf power and network centrality are analyzed. Results show that the individual at the center of the social network may become the key voter because of having more power outside the 'rule power', and a voter with higher 'rule power' may become a weak power person because of being on the edge of a group. The proposed power takes into account the direct and indirect effects of voters, which provides a method to accurately identify key voters. © 2020, Editorial Office of Control and Decision. All right reserved.
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页码：2599 / 2608
页数：9
相关论文
共 23 条
  • [1] Shapley L S, Shubik M., A method for evaluation the distribution of power in a committee system, American Political Science Review, 48, 3, pp. 787-792, (1954)
  • [2] Banzhaf J F., Weighted voting doesn't work: A mathematical analysis, Rutgers Law Review, 19, pp. 317-343, (1964)
  • [3] He D Y, Chen X L, Xu J Q., Weight aggregation method based on principle of minimum cross-entropy in multiple attribute group decision-making, Control and Decision, 32, 2, pp. 378-384, (2017)
  • [4] Wu J, Dai L F, Chiclana F, Et al., A minimum adjustment cost feedback mechanism based consensus model for group decision making under social network with distributed linguistic trust, Information Fusion, 41, pp. 232-242, (2018)
  • [5] Guo C X, Shi R L, Jin M Z., Group decision opinion evolution and simulation based on community and Individual Importance power, Journal of Intelligent and Fuzzy Systems, 33, 5, pp. 2667-2676, (2017)
  • [6] de Blas C S, Martin J S, Gonzalez D G., Combined social networks and data envelopment analysis for ranking, European Journal of Operational Research, 266, 3, pp. 990-999, (2018)
  • [7] Son J, Kim S B., Content-based filtering for recommendation systems using multiattribute networks, Expert Systems with Applications, 89, pp. 404-412, (2017)
  • [8] Huang M X, Wang Q Y, Xiao B M, Et al., A study on the evolutionary mechanism of the idea leader in the consumer advice network of the expectancy clue and the network structure, Management World, 7, pp. 109-121, (2015)
  • [9] Chen X H, Zhao C C, Yang L., A group decision-making model based on interval-valued intuitionistic fuzzy numbers and its application on social network, Systems Engineering — Theory & Practice, 37, 7, pp. 1842-1852, (2017)
  • [10] Gao J, Yang X, Liu D., Uncertain Shapley value of coalitional game with application to supply chain alliance, Applied Soft Computing, 56, pp. 551-556, (2017)
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