Sentiment Analysis for Autistic Children: Understanding Emotional Needs and Experiences
Jawaher Almotiran
College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, AlKharj 11942, Saudi Arabia.
Molka Rekik *
Data Engineering and Semantics Research Unit, Faculty of Sciences of Sfax, University of Sfax, Sfax, Tunisia.
*Author to whom correspondence should be addressed.
Abstract
The proposed system utilizes a Machine Learning (ML) model to analyze and evaluate specific facial attributes that are discriminative for emotion recognition in autistic children. By training the ML model on a dataset of facial images, the system can accurately assess and identify the emotions expressed in the uploaded media, providing recommendations and advice to help users better understand and interact with autistic individuals. By training the ML model on a dataset of facial images, the system can accurately assess and identify the emotions expressed in the uploaded media, providing recommendations and advice to help users better understand and interact with autistic individuals. The recommendation-making process combines machine learning techniques with domain knowledge to provide accurate predictions and useful recommendations for parents of autistic children.
Keywords: Machine learning, deficit hyperactivity disorder, health risks, facial images