Description
The Internet has become an integral part of communication and connectedness between humans. Through social media, it is easier to connect with others and to access resources that improve quality of life. With that it has also posed new challenges, such as the effect it has on users’ mental health. This infodemiologic study proposes to investigate what and how interactions on social media platforms, namely Twitter and Reddit, effect users’ mental health. Infodemiology is the study of the spread of information as it relates to public health, but public health discussions often exclude mental health. The spread of information online has the potential and the risk of affecting the well-being of vulnerable individuals through emotional contagion and triggering information. The ways in which an individual online can mitigate their risk online to improve their mental health and, in turn, the mental health of their online peers is novel and invaluable.The main research question considers the ways in which the diffusion of affective behaviours on the mental health of social media users can be measured and tracked in online social networks, with a focus on depression. The research question is subdivided into three components. The first component is concerned with the linguistic and behavioural attributes of social media users with depression. A thorough analysis of depression-related social media posts from the r/depression subreddit are conducted. The data are extracted and analysed by way of natural language processing techniques, with a particular focus on topic modelling and sentiment analysis. The second component relates to how the attributes obtained from the first component inform online users’ interactions within an online social network. Twitter (currently known as X) data with individuals diagnosed with and without depression are modelled and the interactions within a network are replicated and quantified. The third component is an evaluation of intervention strategies that may be implemented on the network to improve the health of social media users. The modelling of the latter two components involves concepts from social network analytics and agent-based modelling techniques.
Social media research have becoming increasingly challenging to conduct given that access to social media data has been deprecated in recent years. Navigating the challenges of data collection of social media data and the ethical considerations thereof are considered. The techniques applied in this study are a novel contribution to the field of infodemiology and provide a multidisciplinary approach to addressing primarily qualitative research. This study applies the use of state-of-the-art large language models and embedding models within natural language processing. The social network analysis component and simulation modelling component supports the hypothesis that emotional contagion is present in social networks and that there are ways in which the impact of this contagion can be mitigated.
| Period | 2020 → 2025 |
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| Examinee | Kurt Marais |
| Examination held at |
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| Degree of Recognition | International |