Emotional traits classification
The classification resources corresponding to the
emotional-traits taxonomy classify documents in terms of the feelings—joy, surprise, irritation, etc.—expressed in the text. They can recognize 39 different emotional traits1 divided into eight groups.
During the design phase, the choice of which emotional traits to identify was guided—in addition to the developer community needs for this API extension—by the literature available on the subject, including some recent research publications2.
You can find the category tree for this taxonomy in the reference section.
Here is an abstract of the category tree for English:
... Group Dejection Sadness Torment Suffering Sorrow Disappointment Disillusion Resignation Group Surprise Surprise Group Delight Happiness Excitement Joy Amusement Well-Being Satisfaction Relief ...
Classification resources return leaf categories, that is 2nd level categories like Excitement and Disillusion, but if requested with a special parameter they also return the main groups of emotional traits.
Main groups are the taxonomy groups corresponding to the most relevant emotional traits expressed in the text. They provide an easy-to-read indication of the clusters of emotional traits the text is more about, similarly to an abstract.
A. Dabrowski, "Emotions in philosophy. A short introduction", Studia Humana, 2016, 5:3, 8-20.
E. Kim, R. Klinger, "A Survey on Sentiment and Emotion Analysis for Computational Literary Studies", Institut für Maschinelle Sprachverarbeitung, University of Stuttgart, 2018.
A. Yadollahi, A. G. Shahraki, O. S. Zaiane, "Current State of Text Sentiment Analysis from Opinion to Emotion Mining", University of Alberta, 2017.
R. Donovan, A. Johnson, A. deRoiste, R. O'Reilly, "Quantifying the Links between Personality Sub-Traits and the Basic Emotions", Computer Science and its Applications, 2020. ↩