Uncovering Digital Reflections of Depression : Analyzing Social Media Posts for Detecting and Categorizing Depression

This project delves into the detection and categorization of depressive sentiments made by Arabic-speaking Twitter users, which is heavily influenced by cultural stigma in the MENA region. Utilizing a corpus of 10000 tweets from a range of 10 Arabic keywords that are commonly associated with depression, this project uses a binary classification to categorize depressive content. The results depict the tendency of Arab Twitter users to rely on indirect ways of expressing mental health issues that are intertwined with different cultural and societal nuances. Overall, this research acts as a stepping stone for any future machine learning applications, prompting both the development and the refinement of the process of mental health research in the MENA region.