Codes and Datasets for our SIGIR 2021 Paper: "Understanding the Role of Affect Dimensions in Detecting Emotions from Tweets: A Multi-task Approach"
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Updated
Apr 21, 2021 - Jupyter Notebook
Codes and Datasets for our SIGIR 2021 Paper: "Understanding the Role of Affect Dimensions in Detecting Emotions from Tweets: A Multi-task Approach"
This repository contains EmoITA, the first Italian text corpus manually annotated with emotion dimensions according to the Valence-Arousal-Dominance (VAD) model. It has been obtained by translating and re-annotating the EmoBank corpus (Buechel and Hahn, 2017). You can also find files from the EmotivITA shared task at EVALITA 2023.
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