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Found 6 papers, 1 papers with code
Experiencer-Specific Emotion and Appraisal Prediction
Emotion classification in NLP assigns emotions to texts, such as sentences or paragraphs.
Dimensional Modeling of Emotions in Text with Appraisal Theories: Corpus Creation, Annotation Reliability, and Prediction
We analyze the suitability of appraisal theories for emotion analysis in text with the goal of understanding if appraisal concepts can reliably be reconstructed by annotators, if they can be predicted by text classifiers, and if appraisal concepts help to identify emotion categories.
x-enVENT: A Corpus of Event Descriptions with Experiencer-specific Emotion and Appraisal Annotations
In addition, we link them to the event they found salient (which can be different for different experiencers in a text) by annotating event properties, or appraisals (e. g., the perceived event undesirability, the uncertainty of its outcome).
Emotion Stimulus Detection in German News Headlines
Emotion stimulus extraction is a fine-grained subtask of emotion analysis that focuses on identifying the description of the cause behind an emotion expression from a text passage (e. g., in the sentence "I am happy that I passed my exam" the phrase "passed my exam" corresponds to the stimulus.).
Experiencers, Stimuli, or Targets: Which Semantic Roles Enable Machine Learning to Infer the Emotions?
Is it a particular target (everybody loves X) or a stimulus (doing X makes everybody sad)?
Token Sequence Labeling vs. Clause Classification for English Emotion Stimulus Detection
"), and (3) as clause classification ("Does this clause contain the emotion stimulus?").
