With rapid growth of online social network sites, the issue of health-related online communities and its social and behavioral implications has become increasingly important for public health. Unfortunately, online communities often become vehicles for promotion of pernicious misinformation, in particular, that HIV virus is a myth (AIDS denialism). This study seeks to explore online users’ behavior and interactions within AIDS-denialist community to identify and estimate the number of those, who potentially are most susceptible to AIDS-denialist arguments—“the risk group” in terms of becoming AIDS denialists. Social network analysis was used for examining the most numerous AIDS-denialist community (over 15,000 members) in the most popular Russian SNS “ VK.com .” In addition, content analysis was used for collecting data on attitudes toward AIDS-denialist arguments and participants’ self-disclosed HIV status. Two data sets were collected to analyze friendship ties and communication interactions among community members. We have identified the core of online community—cohesive and dedicated AIDS denialists, and the risk group: users who communicate with core members, and, thus, can be more susceptible to the AIDS-denialist propaganda and their health behaviors (e.g., refusing treatment). Analysis allowed to significantly reduce the target audience for possible intervention campaigns and simultaneously increase the accuracy of determining the risk group composition.

The use of social network sites helps people to make and maintain social ties accumulating social capital, which is increasingly important for individual success. There is a wide variation in the amount and structure of online ties, and to some extent this variation is contingent on specific online user behaviors which are to date under-researched. In this work, we examine an entire city-bounded friendship network (N = 194,601) extracted from VK social network site to explore how specific online user behaviors are related to structural social capital in a network of geographically proximate ties. Social network analysis was used to evaluate individual social capital as a network asset, and multiple regression analysis-to determine and estimate the effects of online user behaviors on social capital. The analysis reveals that the graph is both clustered and highly centralized which suggests the presence of a hierarchical structure: a set of sub-communities united by city-level hubs. Against this background, membership in more online groups is positively associated with user's brokerage in the location-bounded network. Additionally, the share of local friends, the number of received likes and the duration of SNS use are associated with social capital indicators. This contributes to the literature on the formation of online social capital, examined at the level of a large and geographically localized population.

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