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Development of Emotion Measurement System Using NoSQL: Integrating Sarcasm Detection with Retrained RoBERTa Model
Annotatsiya
In the rapidly evolving landscape of natural language processing (NLP), accurately
measuring human emotions from textual data is a critical challenge, especially in digital
platforms where nuances like sarcasm can distort interpretations. This research introduces
an Emotion Measurement System (EMS) that integrates NoSQL databases for efficient
handling of unstructured textual data with a fine-tuned RoBERTa model retrained for
sarcasm detection. Sarcasm, marked by ironic contrasts between literal and intended
meanings, frequently causes misclassifications in sentiment and emotion analysis,
impacting applications such as social media monitoring, customer service automation,
and mental health tools.
Kalit so‘zlar
schema to store and query large-scale textual entries
Foydalanilgan adabiyotlar
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