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An Analysis of the Matching Hypothesis in Networks.

Jia T, Spivey RF, Szymanski B, Korniss G - PLoS ONE (2015)

Bottom Line: Our results indicate that the correlation of the couple's attractiveness grows monotonically with the increased average degree and decreased degree diversity of the network.The chance of failing to be matched decreases exponentially with both the attractiveness and the degree.Our results reveal the role of network topology in the process of human mate choice and bring insights into future investigations of different matching processes in networks.

View Article: PubMed Central - PubMed

Affiliation: Social Cognitive Networks Academic Research Center, Rensselaer Polytechnic Institute, Troy, NY, 12180 USA; Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY, 12180 USA; Department of Physics, Applied Physics and Astronomy, Rensselaer Polytechnic Institute, Troy, NY, 12180 USA.

ABSTRACT
The matching hypothesis in social psychology claims that people are more likely to form a committed relationship with someone equally attractive. Previous works on stochastic models of human mate choice process indicate that patterns supporting the matching hypothesis could occur even when similarity is not the primary consideration in seeking partners. Yet, most if not all of these works concentrate on fully-connected systems. Here we extend the analysis to networks. Our results indicate that the correlation of the couple's attractiveness grows monotonically with the increased average degree and decreased degree diversity of the network. This correlation is lower in sparse networks than in fully-connected systems, because in the former less attractive individuals who find partners are likely to be coupled with ones who are more attractive than them. The chance of failing to be matched decreases exponentially with both the attractiveness and the degree. The matching hypothesis may not hold when the degree-attractiveness correlation is present, which can give rise to negative attractiveness correlation. Finally, we find that the ratio between the number of matched couples and the size of the maximum matching varies non-monotonically with the average degree of the network. Our results reveal the role of network topology in the process of human mate choice and bring insights into future investigations of different matching processes in networks.

No MeSH data available.


(a, b) The probability of failing to be matched conditioned on attractiveness a and degree k (Pnot(a, k)) decreases exponentially with a and k in scale-free networks with P(k) ∼ k−γ, γ = 3 and ⟨k⟩ = 5.
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pone.0129804.g003: (a, b) The probability of failing to be matched conditioned on attractiveness a and degree k (Pnot(a, k)) decreases exponentially with a and k in scale-free networks with P(k) ∼ k−γ, γ = 3 and ⟨k⟩ = 5.

Mentions: In fully-connected systems all individuals are able to find their partners. But in networks one faces a chance of failing to be matched. How often it occurs depends on one’s popularity (degree) and attractiveness. Here we consider Pnot(a, k) defined as the probability of failing to be matched conditioned on degree k and attractiveness within the range [a−0.05, a+0.05). We find that Pnot(a, k) drops exponentially with both degree k and attractiveness a. This implies that getting more popular brings the similar benefit as being more attractive in terms of finding a partner (Fig 3).


An Analysis of the Matching Hypothesis in Networks.

Jia T, Spivey RF, Szymanski B, Korniss G - PLoS ONE (2015)

(a, b) The probability of failing to be matched conditioned on attractiveness a and degree k (Pnot(a, k)) decreases exponentially with a and k in scale-free networks with P(k) ∼ k−γ, γ = 3 and ⟨k⟩ = 5.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4470921&req=5

pone.0129804.g003: (a, b) The probability of failing to be matched conditioned on attractiveness a and degree k (Pnot(a, k)) decreases exponentially with a and k in scale-free networks with P(k) ∼ k−γ, γ = 3 and ⟨k⟩ = 5.
Mentions: In fully-connected systems all individuals are able to find their partners. But in networks one faces a chance of failing to be matched. How often it occurs depends on one’s popularity (degree) and attractiveness. Here we consider Pnot(a, k) defined as the probability of failing to be matched conditioned on degree k and attractiveness within the range [a−0.05, a+0.05). We find that Pnot(a, k) drops exponentially with both degree k and attractiveness a. This implies that getting more popular brings the similar benefit as being more attractive in terms of finding a partner (Fig 3).

Bottom Line: Our results indicate that the correlation of the couple's attractiveness grows monotonically with the increased average degree and decreased degree diversity of the network.The chance of failing to be matched decreases exponentially with both the attractiveness and the degree.Our results reveal the role of network topology in the process of human mate choice and bring insights into future investigations of different matching processes in networks.

View Article: PubMed Central - PubMed

Affiliation: Social Cognitive Networks Academic Research Center, Rensselaer Polytechnic Institute, Troy, NY, 12180 USA; Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY, 12180 USA; Department of Physics, Applied Physics and Astronomy, Rensselaer Polytechnic Institute, Troy, NY, 12180 USA.

ABSTRACT
The matching hypothesis in social psychology claims that people are more likely to form a committed relationship with someone equally attractive. Previous works on stochastic models of human mate choice process indicate that patterns supporting the matching hypothesis could occur even when similarity is not the primary consideration in seeking partners. Yet, most if not all of these works concentrate on fully-connected systems. Here we extend the analysis to networks. Our results indicate that the correlation of the couple's attractiveness grows monotonically with the increased average degree and decreased degree diversity of the network. This correlation is lower in sparse networks than in fully-connected systems, because in the former less attractive individuals who find partners are likely to be coupled with ones who are more attractive than them. The chance of failing to be matched decreases exponentially with both the attractiveness and the degree. The matching hypothesis may not hold when the degree-attractiveness correlation is present, which can give rise to negative attractiveness correlation. Finally, we find that the ratio between the number of matched couples and the size of the maximum matching varies non-monotonically with the average degree of the network. Our results reveal the role of network topology in the process of human mate choice and bring insights into future investigations of different matching processes in networks.

No MeSH data available.