Mental Health in Messages

Abstract

In an era dominated by digital communication, textual data offers a treasure of insights into human behaviour and emotions. In today's digitally-driven world, the vast expanse of textual data generated from online interactions serves as a profound indicator of human emotions and behavioural nuances. This research delves deep into the realm of textual sentiment analysis to uncover patterns indicative of mental health states. Through a robust examination of synthetic textual datasets, the study employs advanced techniques to achieve the same. These methods include sentiment analysis, topic modelling, pattern recognition, and emotion detection. By interpreting these digital footprints, this study underscores the potential of textual analysis as a tool not just for understanding, but also for predicting and addressing mental health challenges in digital communication mediums. The findings reveal that digital textual signs can be effective indicators of mental health conditions.