Abstract
INTRODUCTION: Depression is one of the most common mental disorders and one that has a great potential to affect people mentally, physically, and socially. Unfortunately, a majority of people either do not have access to treatment or avoid seeking help. In this context, many platforms have emerged to provide a space for discussion and support where users can interact anonymously. METHODS: This study presents the results of our research on classifying depression in a specific community of religious people by analyzing texts posted on social media using semantic techniques, such as a comparative analysis of texts from users using ontologies. A supporting objective of the research was to create a natural language processing tool for classifying depression to obtain the corpus necessary for ontology creation. RESULTS: The resulting ontologies were analyzed and compared with each other and also with existing ontologies in the literature on general depression. DISCUSSION: The comparison was both qualitative and quantitative, taking into consideration similarity ratios for the quantitative comparison.