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About Emotion Recognition On Twitter Comparative Study and Training A Unison Model PDF
The document presents a study on emotion recognition on Twitter using deep learning techniques. It creates three large datasets of tweets labeled with different emotion classifications. Recurrent neural networks are found to outperform bag-of-words models, with character-based RNNs working better than word-based RNNs. While transfer capabilities between emotion classifications are poor, a single "unison" model is developed that can predict all three classifications and performs comparably to individual models.
Detailed Information
| Author: | ['Naveen Pasupuleti'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 3 |
| Language: | English |
| Format: | |
| Price: | FREE |
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