Network Analysis of HIV-Discourse Inside and Outside of the Groups with HIV Risk

The human immunodeficiency virus (HIV) is a broad and adjacent phenomenon that involves not only medical issues but social components as well. HIV spreading is based on people’s interactions and for us to understand its path we should consider individuals’ health, medical and social practices, and social network of their communications (including with whom they talk, negotiate, have sex, use drugs, etc.). HIV’s diagnosing, treating, and prevention was historically influenced by the way society percept it and due to cultural meanings, people ascribe to it (which predominantly have negative connotations). This view of the problem inevitably shapes the way society reacts to it. That is why our attention will focus on HIV-related discourse. as this is a significant part of how the problem is shaped, perceived, and being solved. As statistics shows, nowadays people from the general population are much more likely to be infected than before and their risks are comparable with key population while previously the possibility of them catching HIV was significantly lower than in key population. The question is “What is the reason for that structural change”? We suppose that prevention practices could be affected by participating in HIV-related discourse, which itself might differ inside and outside HIV risk groups. In our assumption, HIV discourse successfully consolidates efforts of spreading prevention practices among the key populations while among these people discourse is more structured, well-organized, and supported by both discourse founders and participants. What is more, it is important to look at the network of discourse participants. We assume that in key populations people are more likely to stay in touch, develop communication for further mutual help and support which also could lead to an increase of HIV consciousness as a result of strong social ties. Data analysis is going to be divided into two parts: analysis of web data including network data and users’ activity and the questionnaire data. We will consider the networks of users from considered online communities, build networks of their discourse, compare activity and frequency of their commenting and likes gathering, investigate their preventing practices, personal attitude to HIV-related issues, and many other things. In the end, we will make conclusions and underline which particular steps could be done to develop the research further.