This repository contains a sentiment analysis model for detecting mental disorders, specifically suicidal ideation as a symptom of depression from social media posts. It compares BERT with traditional machine learning algorithms for binary classification.
From the README
Automated Depression Detection from Tweets: a Comparison of NLP Techniques Anurag Mahato, Sekharendu Dey, Amitrajit Jana and Shubhadeep Biswas Abstract This paper aims to classify suicidal ideation as a symptom of depression from social media posts by applying the state-of-the-art classification model BERT (Bidirectional Encoder Representations from Transformers) and three traditional machine learning algorithms for binary classification. Since depression is one of the most prevalent mental health disorders amongst psychiatric disorders, the authors intended to present an experimental analysis of the machine learning classifier results as a comparison of novel depression detection...
Skills
- Jupyter Notebook
