Predicting risk profiles of individuals in networks (e.g. susceptibility to a particular disease, or likelihood of smoking) is challenging for a variety of reasons. For one, local' features (such as an individual's demographic information) may lack sufficient information to make informative predictions; this is especially problematic when predicting risk,' as the relevant features may be precisely those that an individual is disinclined to reveal in a survey. Secondly, even if such features are available, they still may miss crucial information, as risk' may be a function not just of an individual's features but also those of their friends and social communities. Here, we predict individual's risk profiles as a function of both their local features and those of their friends. Instead of modeling influence from the social network directly (which proved difficult as friendship links may be sparse and partially observed), we instead model influence by discovering social communities in the network that may be related to risky behavior. The result is a model that predicts risk as a function of local features, while making up for their deficiencies and accounting for social influence by uncovering community structure in the network. We test our model by predicting risky behavior among adolescents from the Add health data set, and hometowns among users in a Facebook ego net. Compared to prediction by features alone, our model demonstrates better predictive accuracy when measured as a whole, and in particular when measured as a function of network "richness."
There are also a number of studies specifically on the role of social networks and risky sexual behavior ( @cite_0 @cite_27 @cite_21 ). However, each of these papers focuses on an individual's interactions with social connections, and how this might affect engaging in risky sexual behavior. In this paper, we examine how entire social communities and the individual's membership or relationship to these communities affects engaging in risky sexual behavior.
@cite_0 @cite_27 @cite_21
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Abstract Although research finds high rates of risky sexual and drug related behavior among homeless young people, little research had examined how the characteristics of their social networks encourage or constrain risky behaviors. Based on a sample of 145 homeless young adults in the Midwestern United States, results revealed that having used alcohol with at least one of their network members and the presence of more conflict was associated with engaging in a greater number of sexual risk taking behaviors. Correlates of engaging in a greater number of substance use related behaviors included having older peers within the network, having used illicit drugs with at least one network member, and the presence of more conflict. The presence of a family member in one’s network, however, was associated with fewer sexual and drug related risk behaviors. Overall, the social network characteristics of youth explained significant, additional variance beyond that of youth’s own characteristics and their early family histories. This article examines how networks of social and sexual relations affect risky sexual behavior and HIV seroprevalence among young gay men. Social networks can transmit information and cultural norms regarding safer sex, while networks of sexual partners channel the risk of exposure to HIV infection. These two network effects may help to explain some of the behavior and seroconversion differentials in the gay community. A number of recent studies have shown higher rates of unsafe sex among younger gay men. In the Longitudinal AIDS Impact Project, for example, younger gay men (18-24) report unsafe receptive anal sex at rates double that for any other age group (30 vs. 14-16 ). One possible explanation is that younger men have watched fewer friends and colleagues contract HIV or AIDS, and are correspondingly less cautious. We test this hypothesis by comparing the personal networks of younger and older gay men to see whether those who practice safer sex have more exposure to persons with HIV or AIDS. The results give only weak support for the hypothesis that personal exposure to the effects of HIV and AIDS increases adherence to safer sex practices. Seroprevalence patterns among young men may be the result of their sexual networks, with those choosing older partners more likely to be exposed to HIV infection. We examine this hypothesis by comparing the age composition of the unsafe sexual partner network for seropositive and seronegative young men. The results strongly support the hypothesis that younger gay men with older partners are the leading edge of the epidemic in their cohort. This paper investigates web users and their sexual behaviors and pornographic self-representations as observed on the sex and dating site http: www.adultfrienfinder.com. The website is a social network and encourages members to find real-life partners for sex whether it be casual sex affairs between singles, swinging couples, or polyamorous extra-marital affairs between “aba” (“attached but available”) individuals and their lovers. The analysis is based on theories of ethnography and social networking and analyzes the effects of corporate networks and homogenizing “sex scripts” on sex lives and Internet culture in Hong Kong. The authors consider processes on social networks that can potentially involve three factors: homophily, or the formation of social ties due to matching individual traits; social contagion, also known as social influence; and the causal effect of an individual’s covariates on his or her behavior or other measurable responses. The authors show that generically, all of these are confounded with each other. Distinguishing them from one another requires strong assumptions on the parametrization of the social process or on the adequacy of the covariates used (or both). In particular the authors demonstrate, with simple examples, that asymmetries in regression coefficients cannot identify causal effects and that very simple models of imitation (a form of social contagion) can produce substantial correlations between an individual’s enduring traits and his or her choices, even when there is no intrinsic affinity between them. The authors also suggest some possible constructive responses to these results.