Leveraging Emotional Intelligence Metrics and NLP-Driven Sentiment Analysis for Predictive Workplace Mental Health Monitoring

Emotion recognition from user-generated text is vital for mental health monitoring, organizational well-being, and social media analytics. We propose a multi-label classification framework leveraging a fine-tuned BERT model to detect overlapping emotional states - joy, sadness, anger, and fear in so...

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Vydané v:	2025 International Conference on Sensors and Related Networks (SENNET) Special Focus on Digital Healthcare(64220) s. 1 - 6
Hlavní autori:	Bhadauriya, Rajvardhan Singh, Shekhar, Kumar Animesh, Jain, Pratham, Vaid, Medha, R, Dhinesh Kumar, A, Rammohan
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 24.07.2025
Predmet:	BERT Bidirectional control Emotion Classification Emotion recognition Encoding Measurement Mental health Monitoring Multi-label Learning Real-time systems Sentiment analysis Social networking (online) UML Unified modeling language
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