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May 3, 2026Open Access

Evaluating Student Emotional Well-Being in Humanitarian Educational Contexts Using an AI-Based Sentiment Analysis System

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Authors

MSMahmoud Galeb Saloum

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Overview

Randomized trial evaluates emotional well-being in humanitarian education, suggesting improved detection through AI analysis.

Key Points

  • This study aims to evaluate student emotional well-being in humanitarian educational contexts using AI-driven sentiment analysis.
  • An AI-based sentiment analysis system was developed utilizing natural language processing and transformer models like BERT and RoBERTa.
  • The system supports multilingual inputs and incorporates real-time alerts and educator guidance for early intervention.
  • Performance was assessed based on its ability to accurately detect emotional states from textual data.
  • The system achieved emotion detection accuracy exceeding 90%, significantly enhancing educators' ability to identify at-risk students.
  • Real-time monitoring enabled timely interventions, contributing to improved student well-being in educational settings.

Cite This Study

Mahmoud Galeb Saloum (2026) studied this question.

synapsesocial.com/papers/69f6e6968071d4f1bdfc7460https://doi.org/10.5281/zenodo.19950844
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