A Transformers Approach to Detect Depression in Social Media

The invention of diverse instant messaging applications or social media platforms has empowered everybody to effortlessly create, widely distribute and convey their views, feelings, innermost thoughts, fears in addition to achievements, with the whole world. With the upgradation of technology like Internet of Things and Artificial Intelligence which are now occupying every single aspect of our human lives. They have made it possible to connect all our devices to each other and operate them with just a single touch and likewise with similar ease, anyone can share and express their opinions, be it in the form of long messages or poems or images on social media platforms like Reddit, Telegram, Facebook, Instagram, Twitter, WhatsApp, etc. This exchange of ideas, views and keeping in touch with each other became all the more important especially in times of Corona when the pandemic forced everyone to stay inside their homes and function from their comfortable environments. The problem of depression became more pronounced in these lockdown times and exacerbated the loneliness of those suffering from mental health disorders. Therefore, early detection of depression through the use of social media information via deep learning techniques can phenomenally revolutionise the area of depression detection, where most of the people took to social media to display their feelings. This paper implements certain baseline models such as Support Vector Machines, Linear Classifiers etc. and the Transformers model on Reddit dataset to thereby, achieve a higher accuracy in detecting depression in social media users.