Emotional Traits Knowledge Model
Overview
The models of the Emotional Traits family categorize documents in terms of the feelings—joy, surprise, irritation, etc.—expressed in the text. They can recognize several different emotional traits divided into eight groups (see the category tree below).
The following models are available:
| Language | Display name |
|---|---|
| English | Emotional Traits EN v# |
| German | Emotional Traits DE v# |
| Italian | Emotional Traits IT v# |
Mostly aimed at documents written in 1st person (tweets, messages, interviews, reviews), but not only, the model can distinguish between relatively subtle differences in emotions.
The model returns leaf categories, that is 2nd level categories like Excitement and Disillusion, but if the Output rules extra data functional option of the workflow block if turned on, it also returns the main groups of emotional traits. Main groups are the category tree 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.
Category tree
Categories are divided in eight groups containing emotions with similar characteristics:
0100 Group Rage
0101 Anger
0102 Irritation
0103 Exasperation
0200 Group Apprehension
0202 Anxiety
0203 Fear
0204 Stress
0205 Worry
0300 Group Distress
0301 Disgust
0302 Repulsion
0311 Guilt
0312 Shame
0313 Embarrassment
0322 Regret
0331 Boredom
0400 Group Resentment
0402 Hatred
0403 Offence
0411 Jealousy
0412 Envy
0500 Group Dejection
0501 Sadness
0502 Torment
0503 Suffering
0511 Disappointment
0512 Disillusion
0513 Resignation
0600 Group Surprise
0601 Surprise
0700 Group Delight
0701 Happiness
0702 Excitement
0703 Joy
0704 Amusement
0705 Well-Being
0711 Satisfaction
0721 Relief
0800 Group Fondness
0801 Like
0802 Trust
0803 Affection
0804 Love
0805 Passion
0812 Empathy
0813 Compassion
0100 Gruppe Ärger
0101 Wut
0102 Gereiztheit
0103 Außersichsein
0200 Gruppe Befürchtung
0202 Angst
0203 Furcht
0204 Stress
0205 Sorge
0300 Gruppe Unbehagen
0301 Ekel
0311 Schuldgefühl
0312 Scham
0313 Verlegenheit
0322 Bedauern
0331 Langeweile
0400 Gruppe Groll
0402 Hass
0403 Beleidigung
0411 Eifersucht
0412 Neid
0500 Gruppe Niedergeschlagenheit
0501 Traurigkeit
0502 Torment
0503 Leiden
0511 Enttäuschung
0513 Resignation
0600 Gruppe Überraschung
0601 Überraschung
0700 Gruppe Vergnügen
0701 Freude
0702 Begeisterung
0704 Belustigung
0705 Wohlsein
0711 Zufriedenheit
0721 Erleichterung
0800 Gruppe Sympathie
0801 Mögen
0802 Vertrauen
0803 Zuneigung
0804 Liebe
0805 Leidenschaft
0812 Einfühlung
0813 Mitgefühl
0100 Rabbia
0101 Ira
0102 Irritazione
0103 Esasperazione
0200 Apprensione
0202 Ansia
0203 Paura
0204 Stress
0205 Preoccupazione
0300 Disagio
0301 Disgusto
0302 Insoddisfazione
0311 Senso di colpa
0312 Vergogna
0313 Imbarazzo
0322 Rimpianto
0331 Noia
0400 Risentimento
0402 Odio
0403 Offesa
0411 Gelosia
0412 Invidia
0500 Sconforto
0501 Tristezza
0502 Tormento
0503 Sofferenza
0511 Delusione
0512 Disillusione
0513 Rassegnazione
0600 Sorpresa
0601 Sorpresa
0700 Appagamento
0701 Felicità
0702 Entusiasmo
0703 Gioia
0704 Divertimento
0705 Benessere
0711 Soddisfazione
0721 Sollievo
0800 Benevolenza
0801 Interesse
0802 Fiducia
0803 Affetto
0804 Amore
0805 Passione
0812 Empatia
0813 Compassione
Note
You may notice that some categories in the tree for English or Italian do not have a correspondent in the tree for German.
The reason is that in German the distinction between some categories is not as clear as other languages, so it was chosen to collapse similar categories:
- 0301 and 0302 → 0301
- 0511 and 0512 → 0511
- 0701 and 0703 → 0701.
Output structure
The model output has the same structure as any other model and is affected by the functional properties of the workflow block.
The peculiar parts of the output are the result of categorization, i.e. the categorization array, and the extraData object: to have extraData it's necessary to turn on the Output rules extra data functional option of the workflow block.
The extraData object contans the main gropus of emotional traits found in the text, for example:
"extraData": {
"groups": [
{
"id": "0500",
"label": "Group Dejection",
"position": 1
}
]
}
Each item of the group array corresponds to a group of emotional traits and has these properties:
| Property | Description |
|---|---|
id |
Identification number or category group name in the category tree |
label |
Group category description |
position |
Ranking of the group |
The group with the highest rank has position set to 1. Other groups, when present, have consecutive values.
Example
Considering the following text:
We're very busy #coding a whole network manager for #unity3d based on #steamworks networking. #gamedev #indiedev #3amDeadTime #horror #game #amusement
The categorization output is:
"categories": [
{
"frequency": 23.06,
"hierarchy": [
"Group Apprehension",
"Fear"
],
"id": "0203",
"label": "Fear",
"namespace": "emotional_traits_en",
"positions": [
{
"end": 133,
"start": 127
}
],
"score": 3,
"winner": true
},
{
"frequency": 76.91,
"hierarchy": [
"Group Delight",
"Amusement"
],
"id": "0704",
"label": "Amusement",
"namespace": "emotional_traits_en",
"positions": [
{
"end": 150,
"start": 141
}
],
"score": 10,
"winner": true
}
]