social_media_emotion_classifier

Overview

social_media_emotion_classifier is a transformer-based NLP model designed to detect emotions in short social media texts such as tweets, comments, and posts. The model classifies text into six common emotional categories.

Model Architecture

The model is built on a BERT-style encoder architecture with a sequence classification head. It processes tokenized text and outputs a probability distribution over predefined emotion labels.

Intended Use

• Emotion detection in social media monitoring
• Sentiment and emotion analytics dashboards
• Content moderation and user behavior analysis
• Research on emotional trends in online communication

Limitations

• Performance may degrade on very long texts
• Emotion interpretation can be subjective
• Not optimized for domain-specific jargon without fine-tuning
• English-language focused