The study examines the relationship between artificial intelligence (AI) and AI-powered social media algorithms. The study aims to determine the relationship between AI technologies integrated with algorithmic systems in social media environments and social media addiction, as well as the factors that could cause addiction among university students. In this context, semi-structured interviews were conducted with twelve university students selected through purposive sampling. The interview data were analysed using descriptive analysis methods in the MaxQDA programme, resulting in three main themes: AI and social media, algorithmic attraction in addiction, and AI-supported addiction. The study, which involved 84 codings, found that AI-supported algorithms extended the time people spent on social media and influenced the formation of echo chambers through the presentation of personalized content. Furthermore, it has been determined that the opportunities offered by AI technologies have accelerated the flow of content production and consumption, causing individuals to experience FOMO and a loss of time control, and that these technologies can cause feelings of loneliness and laziness in users. The study is significant in terms of understanding the impact of the relationship between AI and algorithms on social media environments and emphasising the necessity of conscious social media usage in this regard. Furthermore, the research contains information that supports public health against social media addiction. It is recommended that, in order to raise awareness among university students about how they can use these environments without developing addictive behaviour, the healthy ways of using these systems be incorporated in detail into the educational curriculum within the context of digital literacy.
Demet Yalçın (Thu,) studied this question.
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