Black-Box Emotion Detection: On the Variability and Predictive Accuracy of Automated Emotion Detection Algorithms
Abstract
The current research demonstrates considerable variability in predictive accuracy across major emotion detection systems (such as Google ML or Microsoft Cognitive Services) with lower (higher) classification accuracy for negative (positive) discrete emotions. We provide two modeling strategies to improve prediction accuracy by either combining feature sets or using ensemble...
Paper Details
Title
Black-Box Emotion Detection: On the Variability and Predictive Accuracy of Automated Emotion Detection Algorithms
Published Date
Oct 2, 2020
Journal
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