Bayesian Analysis of Social Influence

The network influence model is a model for binary outcome variables that accounts for dependencies between outcomes for units that are relationally tied. The basic influence model was previously extended to afford a suite of new dependence assumptions and because of its relation to traditional Markov random field models it is often referred to as the auto logistic actor-attribute model (ALAAM). We extend on current approaches for fitting ALAAMs by presenting a comprehensive Bayesian inference scheme that supports testing of dependencies across subsets of data and the presence of missing data. We illustrate different aspects of the procedures through three empirical examples: masculinity attitudes in an all-male Australian school class, educational progression in Swedish schools, and un-employment among adults in a community sample in Australia

Protocol: Mapping social networks, social influence and sexual health among youth in rural KwaZulu-Natal, the Sixhumene cohort study [version 1; peer review: awaiting peer review]

Background: Sexual behaviour and sexually transmitted infections are strongly affected by social connections, and interventions are often adapted more readily when diffused through social networks. However, evidence on how young people acquire ideas and change behaviour through the influence of important social contacts is not well understood in high-HIV-prevalence settings, with the result that past peer-led HIV-prevention interventions have had limited success. / Methods: We therefore designed a cohort study (named Sixhumene or ‘we are connected’) to follow young people in three rural and small-town communities in uMkhanyakude district, KwaZulu-Natal, South Africa, and the people that these youth identify as important in their lives. We will interview them five times over three years, at each visit collecting information on their socioeconomic, social and sexual health lives, and testing them for HIV and herpes simplex virus 2 (HSV-2). We will use this information to understand how these young people’s sexual health decisions are formed. This will include evaluating how poor sexual health outcomes are correlated across social networks, how youth mimic the attitudes and behaviours of those around them, who is at greatest risk of acquiring HIV and HSV-2, and who might be most influential within communities and thus best able to promote protective interventions. / Discussion: The information gathered through this study will allow us to describe social connection and influence spread through these real-world social networks, and how this leads to sexual health outcomes. Sixhumene will provide vital inputs for mathematical models of communities and spreading processes, as well as inform the development of effective interventions to protect the sexual health of community members through appropriate targeting with optimised messaging requiring fewer resources

Protocol: Mapping social networks, social influence and sexual health among youth in rural KwaZulu-Natal, the Sixhumene cohort study

Background: Sexual behaviour and sexually transmitted infections are strongly affected by social connections, and interventions are often adapted more readily when diffused through social networks. However, evidence on how young people acquire ideas and change behaviour through the influence of important social contacts is not well understood in high-HIV-prevalence settings, with the result that past peer-led HIV-prevention interventions have had limited success. Methods: We therefore designed a cohort study (named Sixhumene or ‘we are connected’) to follow young people in three rural and small-town communities in uMkhanyakude district, KwaZulu-Natal, South Africa, and the people that these youth identify as important in their lives. We will interview them five times over three years, at each visit collecting information on their socioeconomic, social and sexual health lives, and testing them for HIV and herpes simplex virus 2 (HSV-2). We will use this information to understand how these young people’s sexual health decisions are formed. This will include evaluating how poor sexual health outcomes are correlated across social networks, how youth mimic the attitudes and behaviours of those around them, who is at greatest risk of acquiring HIV and HSV-2, and who might be most influential within communities and thus best able to promote protective interventions. Discussion: The information gathered through this study will allow us to describe social connection and influence spread through these real-world social networks, and how this leads to sexual health outcomes. Sixhumene will provide vital inputs for mathematical models of communities and spreading processes, as well as inform the development of effective interventions to protect the sexual health of community members through appropriate targeting with optimised messaging requiring fewer resources.</ns3:p