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That makes it possible to study the network of links between buyers and sellers at a level of detail that has never been possible before. Today, Rocha and co reveal the results one such study of prostitute-related activity in Brazil. The community they look at is a public online forum with free registration, financed by advertisements, in which men grade and categorise their sexual encounters with female escorts.
The community appears large with over 10, buyers and more than sellers all of whom use anonymous nicknames. The study covers a period of 6 years from when the community was set up in until The study throws up both expected and unexpected results. Among the expected results is the discovery that the geographical connections between buyers and sellers vary as an inverse square law rather than a power law as in many other internet mediated networks.
Another discovery is that a high rating for a particular sex worker is a good predictor of high ratings in the future. Naturally, buyers tend to use more highly rated sex-workers more often. And over short timescales this can be seen in the data. However, look at longer timescales and the effect drops away. Unexpectedly, these behaviours make the network different from traditional scale free networks in some subtle ways.
That could turn out to be significant. Much work has been done on the spread of disease and one important factor is the nature of the network in which infection takes place. So the questions that is left begging is this: what effect does this have on the spread of sexually transmitted disease? Ref: arxiv. Emerging Technology from the arXiv. Patterns of Prostitution Captured in Social Network.
The patterns of links between buyers and sellers of sex in an online forum differs in important ways from other internet related networks, says a new study. This may have important implications for the spread of sexually transmitted diseases by Emerging Technology from the arXiv. From our advertisers. In association with Intel. Produced in association with IBM.