Depressive and Suicidal Text-Based Sentiment Analysis in Bangla Using Deep Learning Models

This research aims to create and apply efficient sentiment analysis methods for the Bengali language. It also aims to investigate how people in Bangladesh communicate their feelings and mental health issues on social media platforms with a particular emphasis on depression and suicidal thoughts. The process of applying deep learning models to sentiment analysis of suicidal and depressing writing in Bangla entails a few thorough stages. First a dataset of 1076 data points is created by carefully classifying data from a variety of sources including news articles, Facebook, YouTube, and any other online resources into three categories: depressive, non-depressive, and suicidal. Tokenization, stop word removal, and stemming are important preprocessing techniques that help to improve the text. The dataset is…