Abstract

Depression is a real challenge for those who are interested in public health, especially among adolescents and young people. As a result of the tremendous development in the field of technology and the spread of the culture of social networking through the Internet, it became necessary to take advantage of these means in the detection of depression among users of these sites. In this research, we explore the possibility of using social media data to detect and predict depression. In this paper, two Bert transformers were fine-tuned and trained to predict depression in Arabic social media. The proposed models presented a promising performance in comparison with the previous study on the same dataset.

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