Detecting depression from social networks using natural language processingTavchioski, Ilija (Avtor) Robnik Šikonja, Marko (Mentor) Pollak, Senja (Komentor) Natural Language ProcessingTransformersDepression DetectionThe rapid technological advances in the past two decades have drastically affected our society's behavior, culture, and lifestyle. Social media, as one of the many products of this phenomenon, become an essential part of our lives as a tool for communication and expression. Social media become a popular choice for people to share information with the community, such as their thoughts and feelings on various matters in their lives. This especially can be observed in people with mental health issues, such as depression. They often prefer to express their strong feelings or ask for advice on social media. Social media posts also offer a possibility for automatically detecting signs of depression. In this thesis, we present the solution to this problem using natural language processing methods on two different data sets which are composed of posts from the social platforms Reddit and Twitter. We propose using large pre-trained models such as the BERT model and the use of transfer learning between the two data sets. We additionally improved the results by creating an ensemble of several combinations of transformer-based models pre-trained on different domains.20222022-09-13 19:10:00Diplomsko delo/naloga140245sl