Two-way selection on complex weighted networks
- 163 Downloads
The phenomena of two-way selection among people are universal. In the paper, we depict the model of two-way selection in complex weighted networks and give its mathematical theory tools for uncovering the dynamics of human behaviors. We present two definitions: direct matching and indirect matching, which exist in social life. Based on priority, we give two different methods that how an individual to find a match object. In the former case, we consider an individual’s neighbors as his selections. In the latter case, based on the Markov process we develop a method that how an individual to find a match object through its neighbors in complex weighted networks. Our framework is of both fundamental and practical interest, as it provides a novel understanding of the interplay between weighted networks and two-way selection.
KeywordsTwo-way selection Complex weighted networks Preference Matching Modeling
We would like to thank Z.M. Gao for many interesting and inspiring discussions. We wish to express our sincere appreciation to all those who made suggestions for improvements to this paper. Particularly, we thank Y.P. Liang with expertise in technical English editing for the English of this manuscript being improved.
This work was supported by Innovation Foundations of Education for Graduate Students of Shanxi Province (Grant No. 2016BY061) and the National Natural Science Foundation of China (Grant Nos. 61402319, 61503271). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
YY conceived and designed the research, analyzed and described the analytic model, wrote the paper, prepared figures, performed the computation work. GX conceived and designed the research, analyzed the data, reviewed drafts of the paper.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
- 2.Clements M, Serdyukov P, de Vries AP, Reinders MJT (2011) Personalised travel recommendation based on location co-occurrence. arXiv preprint arXiv:1106.5213
- 3.Shang M-S, Lǔ L-Y, Zhang Y-C, Zhou T (2010) Empirical analysis of web-based user-object bipartite networks. Europhys Lett 90(4):48006Google Scholar
- 4.Qi X, Du F, Wu T-J (2009) Empirical analysis of Internet telephone network: from user ID to phone. Chaos Interdiscipl J Nonlinear Sci 19(2):023101Google Scholar
- 5.Oméro MJ, Dzierzawa M, Marsili M, Zhang Y-C (1997) Scaling behavior in the stable marriage problem. J Phys I 7(12):1723–1732 Google Scholar
- 6.Zhou B, Qin S-J, Han X-P, He Z, Xie J-R, Wang B-H (2014) A model of two-way selection system for human behavior. PLoS ONE 9(1):e81424Google Scholar
- 7.Zhou B, He Z, Jiang L-L, Wang N-X, Wang B-H (2014) Bidirectional selection between two classes in complex social networks. Sci Rep 4:7577Google Scholar
- 10.Celik OB, Knoblauch V (2007) Marriage matching with correlated preferences. Economics Working Papers, 200716Google Scholar
- 11.Alejandro L-C, Mulet R (2006) The marriage problem: from the bar of appointments to the agency. Phys A Stat Mech Appl 364:389–402Google Scholar
- 13.Mourifié I, Siow A (2014) Cohabitation versus marriage: marriage matching with peer effects. Available at SSRN 2541895Google Scholar
- 15.Lu J-K, Fan L-C, Luo W-D (2015) The impact of mass media on divorce rate: an empirical study-based on the provincial panel data of China. Popul Res 39(2):67–77Google Scholar
- 16.Jia Z-K, Feng X-T (2013) Contemporary urban youth’s criteria of mate selection-based on the empirical analysis of a nanjing ten thousand people blind date. J Hebei Univ (Philos Soc Sci) 38(2):91–96Google Scholar
- 17.Sun P-D (2013) Match-making corner and parental match-making: in the perspective of collective anxieties of the parents who have had ZHIQING. Youth Stud 6:12–25Google Scholar
- 22.Gabrielli A, Caldarelli G (2007) Invasion percolation and critical transient in the Barabási model of human dynamics. Phys Rev Lett 98(20):208701Google Scholar
- 23.Viswanathan GM, Buldyrev SV, Havlin S et al (1999) Optimizing the success of random searches. Nature 401(6756):911–914Google Scholar
- 24.Vazquez A (2005) Exact results for the Barabsi model of human dynamics. Phys Rev Lett 95(24):248701Google Scholar
- 25.Oliveira JG, Vazquez A (2009) Impact of interactions on human dynamics. Phys A Stat Mech Appl 388(2):187–192Google Scholar
- 26.Masuda N, Kim JS, Kahng B (2009) Priority queues with bursty arrivals of incoming tasks. Phys Rev E 79(3):036106Google Scholar
- 27.Zhou T, Ren J, Medo M, Zhang Y-C (2007) Bipartite network projection and personal recommendation. Phys Rev E 76(4):046115Google Scholar
- 28.Resnick P, Varian HR (1997) Recommender systems. Commun ACM 40(3):56–58Google Scholar
- 29.Lü L-Y, Medo M, Yeung C-H, Zhang Y-C, Zhang Z-K, Zhou T (2012) Recommender systems. Phys Rep 519(1):1–49Google Scholar
- 32.Coviello L, Franceschetti M, McCubbins MD et al (2012) Human matching behavior in social networks: an algorithmic perspective. PLoS ONE 7(8):e41900Google Scholar
- 33.Kearns M, Suri S, Montfort N (2006) An experimental study of the coloring problem on human subject networks. Science 313(5788):824–827Google Scholar
- 34.Kearns M, Judd S, Tan J et al (2009) Behavioral experiments on biased voting in networks. Proc Natl Acad Sci 106(5):1347–1352Google Scholar