Emotion helps Sentiment: A Multi-task Model for Sentiment and Emotion Analysis
TABLE IV: Comparison with the state-of-the-art systems proposed by [16] on emotion dataset. The metrics P, R and F stand for Precision, Recall and F1-Score.
['[BOLD] Models', 'Metric', '[BOLD] Emotion Anger', '[BOLD] Emotion Anticipation', '[BOLD] Emotion Disgust', '[BOLD] Emotion Fear', '[BOLD] Emotion Joy', '[BOLD] Emotion Sadness', '[BOLD] Emotion Surprise', '[BOLD] Emotion Trust', '[BOLD] Emotion Micro-Avg']
Overall, our proposed system achieves an improvement of 5 F-Score points over the existing state-of-the-art system for emotion analysis. Individually, the proposed system improves the existing F-scores for all the emotions except surprise. This could be attributed to the data scarcity and a very low agreement between the annotators for the emotion surprise.