Limits...
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.


The Pearson coefficient of correlation ρ of the attractiveness between the two coupled individuals in Erdős-Rényi networks with size 2N (N = 10,000) and varying average degree ⟨k⟩.ρ increases monotonically in all three cases analyzed. However, ρ is largest in networks where the degree and the attractiveness are positively correlated. When they are negatively correlated, ρ is weakest and can even be negative.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4470921&req=5

pone.0129804.g004: The Pearson coefficient of correlation ρ of the attractiveness between the two coupled individuals in Erdős-Rényi networks with size 2N (N = 10,000) and varying average degree ⟨k⟩.ρ increases monotonically in all three cases analyzed. However, ρ is largest in networks where the degree and the attractiveness are positively correlated. When they are negatively correlated, ρ is weakest and can even be negative.

Mentions: So far we have concentrated only on cases where there is no correlation between one’s popularity (degree) and attractiveness. In reality these two features are often correlated. On one hand, the positive correlation is somewhat expected as a highly attractive person can potentially be also very popular hence having a larger degree. On the other hand, negative correlation could also occur when those with low attractiveness are more active in making friends to balance their disadvantage in attractiveness. We extend our analysis to two extreme cases when degree and attractiveness are correlated (see Method). For a given network topology, the correlation of attractiveness (ρ) is strongest when the degree and the attractiveness are positively correlated and weakest when they are negatively correlated. It is noteworthy that with negative degree-attractiveness correlation, ρ can become negative in networks with low ⟨k⟩, suggesting that the matching hypothesis may not hold in such networks even though the underlying mechanism does not change (Fig 4).


An Analysis of the Matching Hypothesis in Networks.

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

The Pearson coefficient of correlation ρ of the attractiveness between the two coupled individuals in Erdős-Rényi networks with size 2N (N = 10,000) and varying average degree ⟨k⟩.ρ increases monotonically in all three cases analyzed. However, ρ is largest in networks where the degree and the attractiveness are positively correlated. When they are negatively correlated, ρ is weakest and can even be negative.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0129804.g004: The Pearson coefficient of correlation ρ of the attractiveness between the two coupled individuals in Erdős-Rényi networks with size 2N (N = 10,000) and varying average degree ⟨k⟩.ρ increases monotonically in all three cases analyzed. However, ρ is largest in networks where the degree and the attractiveness are positively correlated. When they are negatively correlated, ρ is weakest and can even be negative.
Mentions: So far we have concentrated only on cases where there is no correlation between one’s popularity (degree) and attractiveness. In reality these two features are often correlated. On one hand, the positive correlation is somewhat expected as a highly attractive person can potentially be also very popular hence having a larger degree. On the other hand, negative correlation could also occur when those with low attractiveness are more active in making friends to balance their disadvantage in attractiveness. We extend our analysis to two extreme cases when degree and attractiveness are correlated (see Method). For a given network topology, the correlation of attractiveness (ρ) is strongest when the degree and the attractiveness are positively correlated and weakest when they are negatively correlated. It is noteworthy that with negative degree-attractiveness correlation, ρ can become negative in networks with low ⟨k⟩, suggesting that the matching hypothesis may not hold in such networks even though the underlying mechanism does not change (Fig 4).

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.