An Analysis of new media ecology in the context of algorithmic culture

The aim of this thesis is to investigate how algorithmic culture affects and shapes the new media ecology within the framework of General System Theory and Affordances Theory. For this purpose, firstly, a detailed literature analysis was made on the research topic, and then the research was carried out based on the General Systems Theory and Affordances Theory. A matrix was created based on the basic features of the two theories and open-ended questions created from this matrix were used as a data collection tool. Within the scope of the research designed as a qualitative case study, the data obtained from semi-structured interviews conducted face-to-face and online with ten people who produce content on the YouTube platform were examined with the help of the MAXQDA qualitative analysis program. As a result of the thematic analysis, twelve themes related to three main themes and twenty-eight sub-themes related to these themes were identified. The findings obtained through thematic analysis were evaluated in relation to the theoretical basis and literature. Based on the findings, it can be said that the YouTube algorithm creates positive feedback loops, causing an ecosystem that standardizes and reduces diversity on the platform.