Well its sounds totally insane!. How can any mathematical model of complex networks govern of how we select our mating partners? Can animal instincts be modeled like that?Can we fight HIV more effectively just by observing some graph on a paper?.... really its a long list of intriguing questions.
Well for starters this is a mystery and this blog entry attempts to shed some light into it.
A sexual network is a social network that is defined by the sexual relationships within a set of individuals where an individual is a node and links represent sexual interactions. Sexual networks can be used to describe the sexual interactions in animal populations and reveal which individuals are directly competing in the mating game 
These 'sexual networks' can unlock how sexual selection operates in animal societies where females often mate with multiple males(strange! but blame it totally on research findings... :P). The network-based approach could also help to study the spread of sexually-transmitted diseases.
For centuries naturalists believed that most organisms played a very simple mating game in which a subset of males and females in the population would form monogamous reproductive pairs.Charles Darwin himself identified sexual selection, the selection of this successful subset, as the agent responsible for the evolution of a bewildering diversity of extravagant traits utilized in competition over reproductive opportunities.
Yet recent studies have undermined this simple view of sexual interactions. They show that, far from being monogamous, females often mate with multiple males – a process called polyandry – and that the sexual dynamics within polyandrous societies are typically highly-structured with sexual interactions being far from random as individuals choose and compete over mates within non-random groups.
By using the information gained from studying 'sexual networks' we can dissect the way that sexual selection operates on a particular trait both in the local and global population.This paper demonstrates that this new approach allows for more accurate estimates of sexual selection particularly at intermediate levels of polyandry. We can also use our approach to examine the spread and impact of sexually-transmitted diseases across a particular population.
The issue shows how polyandry is emerging as a lens through which scientists can better resolve their understanding of a diverse range of ecological and evolutionary processes, from selfish genetic elements to extinction risk and conservation.
For the first time, complex network scientists have mapped the romantic and sexual relationships of an entire high school over 18 months, providing evidence that these adolescent networks may be structured differently than researchers previously thought.
The results showed that, unlike many adult networks, there was no core group of very sexually active people at the high school. There were not many students who had many partners and who provided links to the rest of the community.
Instead, the romantic and sexual network at the school created long chains of connections that spread out through the community, with few places where students directly shared the same partners with each other. But they were indirectly linked, partner to partner to partner. One component of the network linked 288 students – more than half of those who were romantically active at the school – in one long chain. (See figure for a representation of the network.)
Research finding compares this network to rural phone lines, running from a long main trunk line to individual houses. As a comparison, many adult sexual networks are more like an airline hub system where many points are connected to a small number of hubs but indeed it is a very different kind of network.
The results have implications for designing policies to stop the spread of sexually transmitted diseases among adolescents.
The most striking feature of the network was a single component that connected 52 percent of the romantically involved students.This means student A had relations with student B, who had relations with student C and so on, connecting all 52%(288/554) of these students.While this component is large, it has numerous short branches and is very broad – the two most distant individuals are 37 steps apart. (Or to use a currently popular term, there were 37 degrees of separation between the two most-distant students :P)
From a student’s perspective, a large chain like this would boggle the mind.They might know that their partner had a previous partner. But they don’t think about the fact that this partner had a previous partner, who had a partner, and so on.What this showed is that there are many of these links in a chain, going far beyond what anyone could see and hold in their head.
Outside of this large component, there were numerous other smaller components in the network . There were 63 simple pairs – two individuals whose only partnership was with each other.All told, only 35 percent of the romantically active students (189) were involved in networks containing three or fewer students. There were very few components of intermediate size (4 to 15) students.
While many students were connected to much larger networks, they probably didn’t see it that way. In fact, they probably had no idea of their connections to the network.Many of the students only had one partner. They certainly weren’t being promiscuous. But they couldn’t see all the way down the chain.
The surprising thing about the network was the near absence of cycling –- situations in which people have relationships with others close to them on the network.
The lack of cycling seems traceable to rules that adolescents have about who they will not date. The teens will not date (from a female perspective) one’s old boyfriend’s current girlfriend’s old boyfriend. This would be considered taking “seconds” in a relationship.
If you break up with someone, you may want to get as away from them as possible in your next relationship. You don’t want to be connected to them in some way by dating someone with a close relationship.
The practical result from such a rule is that no cores form, and that long, chain-like networks form instead. That has important implications for preventing the spread of STDs in teenage populations.
In adult populations, in which there are cores of sexually active people who are the main conduits of disease, you can focus education and other efforts to this select group.
But in the case of adolescents there aren’t any hubs to target, so you have to focus on broad-based interventions.
This also means it matters less which people you reach with your efforts. Networks such as the one discussed are extremely fragile and just breaking one link in the chain – any link - will stop that part of the network from spreading any further. If enough links are broken, the spread of STDs can be radically limited.
Focusing on risk behavior alone does not explain why some persons and communities continue to be infected with HIV and other sexually transmitted diseases (STDs) more than others. Networks help explain why persons can have the same risk behavior and yet one may have a much greater risk of contracting or transmitting HIV.
Hope this gives the reader a useful insight into the world of ‘Sexual Networks’ and the sheer power of Complex Networks.
(1)Chains of Affection: The Structure of Adolescent Romantic and Sexual Networks
by: Peter S. Bearman, James Moody, Katherine Stovel,American Journal of Sociology, Vol. 110, No. 1. (July 2004), pp. 44-91
(2) R.J. Thorton, ‘Preventing AIDS: A new paradigm for a new strategy’, 2008,http://wiredspace.wits.ac.za.
(3) Reinking, D., et al., 1994. Social transmission routes of HIV: A combined and life course perspective. Patient Education and Counseling, 24, pp.289-297.
(4) ‘Sexual networks and STI: A brief overview’, Centre for Health Training, 2009,http://www.centerforhealthtraining.org.
(5) D. Wohlfeiler and J. Potterat, ‘How do sexual networks affect HIV/STD prevention?’, 2003,http://caps.ucsf.edu; Adimora, A.A., and Schoenbach, V.J., 2005. Social context, sexual networks, and racial disparities in rates of sexually transmitted infections. Journal of Infectious Diseases, 191(1), pp. 115-122.
(6) Liljeros, F., Edling, C.R., and Nunes Amaral, L.A., 2003. Sexual networks: Implications for the transmission of sexually transmitted infections. Microbes and Infection, 5, pp.189–196.
(7) Mah, T., and Halperin, D., 2010. Concurrent sexual partnerships and the HIV epidemics in Africa: Evidence to move forward. AIDS and Behavior, 14(1), pp.11-16.
(8) ‘Expert think tank meeting on HIV prevention in high-prevalence countries in southern Africa’, SADC, 2008, http://www.sadc.int.
(9) Shelton, J.D., 2009. Why multiple sexual partners? The Lancet, 374, pp.367-69; Kenyon, C., Boulle, A., Badri, M., and Asselman, V., 2010 Journal of Social Aspects of HIV/AIDS, 7(3), pp.36-43.
(10) Wikipedia: http://en.wikipedia.org/wiki/Sexual_network