feel it italian sentiment EU AI Act Compliance Profile

FEEL-IT: Emotion and Sentiment Classification for the Italian Language

FEEL-IT Python Package

You can find the package that uses this model for emotion and sentiment classification here it is meant to be a very simple interface over HuggingFace models.

License

Users should refer to the following license

Abstract

Sentiment analysis is a common task to understand people's reactions online. Still, we often need more nuanced information: is the post negative because the user is angry or because they are sad?

An abundance of approaches has been introduced for tackling both tasks. However, at least for Italian, they all treat only one of the tasks at a time. We introduce FEEL-IT, a novel benchmark corpus of Italian Twitter posts annotated with four basic emotions: anger, fear, joy, sadness. By collapsing them, we can also do sentiment analysis. We evaluate our corpus on benchmark datasets for both emotion and sentiment classification, obtaining competitive results.

We release an open-source Python library, so researchers can use a model trained on FEEL-IT for inferring both sentiments and emotions from Italian text.

| Model | Download | | ------ | -------------------------| | feel-it-italian-sentiment | Link | | feel-it-italian-emotion | Link |

Model

The feel-it-italian-sentiment model performs sentiment analysis on Italian. We fine-tuned the UmBERTo model on our new dataset (i.e., FEEL-IT) obtaining state-of-the-art performances on different benchmark corpora.

Data

Our data has been collected by annotating tweets from a broad range of top

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