47 citations · 71 across the 3 of their papers we have counts for
4 papers
Dimensional Modeling of Emotions in Text with Appraisal Theories: Corpus Creation, Annotation Reliability, and Prediction
Enrica Troiano, Laura Oberländer, Roman Klinger
The most prominent tasks in emotion analysis are to assign emotions to texts and to understand how emotions manifest in language. An observation for NLP is that emotions can be com…
x-enVENT: A Corpus of Event Descriptions with Experiencer-specific Emotion and Appraisal Annotations
Enrica Troiano, Laura Oberländer, Maximilian Wegge +1
Emotion classification is often formulated as the task to categorize texts into a predefined set of emotion classes. So far, this task has been the recognition of the emotion of wr…
Token Sequence Labeling vs. Clause Classification for English Emotion Stimulus Detection
Laura Oberländer, Roman Klinger
Emotion stimulus detection is the task of finding the cause of an emotion in a textual description, similar to target or aspect detection for sentiment analysis. Previous work appr…
Experiencers, Stimuli, or Targets: Which Semantic Roles Enable Machine Learning to Infer the Emotions?
Laura Oberländer, Kevin Reich, Roman Klinger
Emotion recognition is predominantly formulated as text classification in which textual units are assigned to an emotion from a predefined inventory (e.g., fear, joy, anger, disgus…