README.md

metadata

license: mit
task_categories:
  - text-classification
language:
  - en
tags:
  - emotion
  - affect
pretty_name: OME
size_categories:
  - 1K<n<10K

Orthogonal Model of Emotions

Abbreviated: OME

The baseline OME dataset has 47 categories for classifying emotion in English language examples from a curated dataset deriving emotional clusters using dimensions of Subjectivity, Relativity, and Generativity. Additional dimensions of Clarity and Acceptance were used to map seven population clusters of ontological experiences categorized as Trust or Love, Happiness or Pleasure, Sadness or Trauma, Anger or Disgust, Fear or Anxiety, Guilt or Shame, and Jealousy or Envy.

Author

C.J. Pitchford

Creation Date

Originally created 2016, first version published September, 2017, at Medium.

Version

v4.2

Categories

[Clusters listed in brackets (alphabetically) organize the dataset, but aren't labels]

• [Anger or Disgust]
  • anger-maybe
  • anger-partial
  • anger-quite
  • anger-really
  • anger-very
  • anger-xtreme
• [Fear or Anxiety]
  • fear-maybe
  • fear-partial
  • fear-quite
  • fear-really
  • fear-very
  • fear-xtreme
• [Guilt or Shame]
  • guilt-maybe
  • guilt-partial
  • guilt-quite
  • guilt-really
  • guilt-very
  • guilt-xtreme
• [Happiness or Pleasure]
  • happiness-maybe
  • happiness-partial
  • happiness-quite
  • happiness-really
  • happiness-very
  • happiness-xtreme
• [Jealousy or Envy]
  • jealousy-maybe
  • jealousy-partial
  • jealousy-quite
  • jealousy-really
  • jealousy-very
  • jealousy-xtreme
• [Neutral or Edge Cases]
  • more-negative-than-positive
  • more-positive-than-negative
  • negative
  • neutral
  • positive
• [Sadness or Trauma]
  • sadness-maybe
  • sadness-partial
  • sadness-quite
  • sadness-really
  • sadness-very
  • sadness-xtreme
• [Trust or Love]
  • trust-maybe
  • trust-partial
  • trust-quite
  • trust-really
  • trust-very
  • trust-xtreme

Baseline Model

The baeline model was created using Transformers and PyTorch.