How did you build your emotional dictionary ? Do you have a few examples ?

How did you build your emotional dictionary ? Do you have a few examples ?

To perform emotion recognition in customer comments, Q°emotion has developed its own methodology based on its own assets and technology.

We use an unique emotional dictionary and advanced NLP algorithms that enables distinguish the emotional intensity markers with accuracy.

Let's have a look on how it was built:

The emotional dictionary from Q°emotion is a proprietary emotional corpus that have been build in 3 steps:

1. We based the primitive dictionary on the ANEW (Affective Norms for English Words, Bradley and Lang (1999)).

For every word, the emotional intensity indicator is calculated based the maximum arousal scoring observed in the speech, using scientific affective norms developed for each idioma.

Affective norms have been indeed proposed in several languages in the 80`s. The evaluations were done in the dimensions of valence, arousal and dominance using the Self-Assessment Manikin (SAM), and normalized. The precised methodology has been precisely defined for English (ANEW = Affective norms on English Words) and is followed for other languages (FAN=French Affective Norms, ANGST=Affective norms for German Sentiment terms). The dataset has also been replicated in other languages such as Portuguese (Soares et al., 2012), Italian (Montefinese et al., 2014), or Spanish (Redondo et al., 2007).