Location
https://www.kennesaw.edu/ccse/events/computing-showcase/sp24-cday-program.php
Document Type
Event
Start Date
25-4-2024 4:00 PM
Description
Mental health is a critical aspect of our overall well-being. Mental illness refers to conditions that impact an individual's psychological state, resulting in considerable distress, and limitations in functioning day-to-day tasks. Due to the progress of technology, social media has merged as the platform, for individuals to share their thoughts and emotions. The psychological state of individuals can be accessed with the help of data from these platforms. However, it is challenging for conventional machine learning models to analyze the diverse linguistic contexts of social media data. In this work, we propose a novel attention-driven deep framework to overcome these challenges. Our proposed framework utilizes multi-level (word, sentence, and document) data to identify the causes behind mental illness. The efficacy and effectiveness of our proposed model are shown by extensive evaluation on Reddit data. The insights from this research deepen our understanding of different factors behind mental illness and would aid mental health professionals in formulating effective interventions.
Included in
GPR-16 Attention Driven Framework for Detecting Mental Illness Causes from Social Media
https://www.kennesaw.edu/ccse/events/computing-showcase/sp24-cday-program.php
Mental health is a critical aspect of our overall well-being. Mental illness refers to conditions that impact an individual's psychological state, resulting in considerable distress, and limitations in functioning day-to-day tasks. Due to the progress of technology, social media has merged as the platform, for individuals to share their thoughts and emotions. The psychological state of individuals can be accessed with the help of data from these platforms. However, it is challenging for conventional machine learning models to analyze the diverse linguistic contexts of social media data. In this work, we propose a novel attention-driven deep framework to overcome these challenges. Our proposed framework utilizes multi-level (word, sentence, and document) data to identify the causes behind mental illness. The efficacy and effectiveness of our proposed model are shown by extensive evaluation on Reddit data. The insights from this research deepen our understanding of different factors behind mental illness and would aid mental health professionals in formulating effective interventions.