Emotion Detection in Text: Latest Developments and Challenges

Explore the latest developments in emotion detection from text in this 33-minute conference talk from HLTCon 2021. Delve into the complexities of computational emotion representation, including discrete categories and the valence-arousal-dominance (VAD) spectrum. Learn about existing emotion-detection techniques, available datasets, and the challenges of implementing production-level emotion detection systems. Discover how emotion detection can enhance applications like opinion mining and mental health diagnosis. Gain insights into the multidimensional nature of emotions compared to one-dimensional sentiment analysis. Examine various models for representing emotions, including the RAS and VAD models. Address challenges such as metaphor interpretation and misinformation in emotion detection. Conclude with a Q&A session to deepen your understanding of this cutting-edge natural language processing application.

Intro
What is Emotion
Representing Emotions
Dimensional Approach
RAS Model
VAD Model
Challenges
Metaphors
Misinformation
Questions