feel-ic-ita-emotion: Emotion Classification for the Italian Jornalistic Language (forthcoming)
Paride Carrara & Simon Luck
This model is a fine-tuned Italian emotion classification model designed to categorise sentences into five classes: fear, sadness, anger, joy, and neutral. It has been trained on a corpus of sentences extracted from Italian newspaper articles from La Repubblica, Il Giornale, and Il Sole 24 Ore, making it especially well-suited for emotion detection in formal and journalistic Italian text.
feel-ic-ita-sentiment: Sentiment Analysis for the Italian Journalistic Language (forthcoming)
Paride Carrara & Simon Luck
The name feel-ic-ita is derived from the Italian word felicità, meaning "joy" in English, reflecting the model's emphasis on performing sentiment analysis on the Italian language. This model is a fine-tuned Italian sentiment classification model designed to categorise sentences into three classes: positive, negative, and neutral. The sentiment categories are derived by grouping emotions from the original emotion model feel-ic-ita-emotion: joy is considered positive; fear, sadness, and anger are grouped as negative; and neutral remains unchanged.
