Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Languages:
English
Size:
10K - 100K
License:
Update README.md
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# Orthogonal Model of Emotions
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Abbreviated: OME
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The fifth version of the OME dataset has 26 categories for classifying emotion in English language examples in a curated dataset deriving emotional clusters using dimensions of Subjectivity, Relativity, and Generativity. Additional dimensions of Clarity, now simpler with three levels, and Compassion, using rate of change to linearize the data, were used to map seven population clusters of ontological experiences categorized as Trust or Love, Happiness or Pleasure, Jealousy or Envy, Shame or Guilt, Anger or Disgust, Fear or Anxiety, and Sadness or Trauma. Edge cases, neutrality, and simple sentiments, such as positive and negative, are also used as null cases in classification theorized by OME.
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# Orthogonal Model of Emotions
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Abbreviated: **OME**
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The fifth version of the OME dataset has 26 categories for classifying emotion in English language examples in a curated dataset deriving emotional clusters using dimensions of Subjectivity, Relativity, and Generativity. Additional dimensions of Clarity, now simpler with three levels, and Compassion, using rate of change to linearize the data, were used to map seven population clusters of ontological experiences categorized as Trust or Love, Happiness or Pleasure, Jealousy or Envy, Shame or Guilt, Anger or Disgust, Fear or Anxiety, and Sadness or Trauma. Edge cases, neutrality, and simple sentiments, such as positive and negative, are also used as null cases in classification theorized by OME.
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