Abstract:
Depression as a mental health problem is emerging as a serious problem in the
world, while people take social networks as the only place where they can share
their feelings and experiences. Identifying depressive comments in SNS can help
find those people in need primary intervention to prevent the disease(s). As there
is scarce literature on mental health prediction using Bangla text, this study
aims to build a Bangla depressive comment detection system using machine
learning and deep learning algorithm. This system works on a dataset of 3420
Bangla social media comments classified into Depressive and Non-Depressive.
Categorized into main categories that are the classic methods including: SVM,
Logistic Regression and Decision Trees, the deep learning methods like LSTM
networks and CNNs. The proposed models are designed to predict depressive
comments, keeping in mind the dispersed features of regular Bangla text. The
assessment of the system is done comprehensively where parameters such as
accuracy, precision, recall and F1-score are used in measuring the efficiency of
several models.
