EMOTIDROID: Harnessing Machine Learning for Web-Based Emotion Detection in Non-Person Images on X

Author : Aliff Aiman Muhamad Ridzuan, Assoc. Prof. Dr. Siti Hafizah Ab Hamid, Laili Mardziah Tajuddin, Fatin Nur Jannah Muhamad

Abstract :Mental health presents an increasingly critical issue, with social media platforms, particularly X, serving as venues for individuals to share experiences and seek support. The overwhelming influx of information on such platforms often overwhelms those struggling with mental health concerns. In response, the EMOTIDROID web-based application, developed using deep learning algorithms, analyzes emotions conveyed through non-person images posted on social media. EMOTIDROID predicts the emotional content of these images, identifies potential mental health issues, and offers personalized interventions. The system conducts emotion analysis based on social media data, providing users insights into their emotional states and suggesting mental hygiene practices. This approach fosters a safer online environment by mitigating risks related to harmful content and delivering timely support for mental well-being.

Keywords :Emotion Recognition, Emotion Detection, Machine Learning, CNN, Web-Based.

Conference Name :International Conference on Advanced Computer Science and Information Technology (ICACSIT-24)

Conference Place Kuala Lumpur, Malaysia

Conference Date 6th Dec 2024