EmoScan: Automatic Screening of Depression Symptoms in Romanized Sinhala Tweets

arXiv:2403.19728v1 Announce Type: cross
Abstract: This work explores the utilization of Romanized Sinhala social media data to identify individuals at risk of depression. A machine learning-based framework is presented for the automatic screening of depression symptoms by analyzing language patterns, sentiment, and behavioural cues within a comprehensive dataset of social media posts. The research has been carried out to compare the suitability of Neural Networks over the classical machine learning techniques. The proposed Neural Network with an attention layer which …

abstract arxiv cs.cl cs.cy cs.lg data dataset depression framework identify language machine machine learning media media data patterns risk screening sentiment social social media tweets type work