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metadata
language:
  - it
task_categories:
  - text-classification

Dataset: sentiment_analysis-IT-dataset

Dataset Description

Our data has been collected by annotating tweets on Italian language from a broad range of topics. In total, we have 2037 tweets annotated with an emotion label. More details can be found in our paper (https://aclanthology.org/2021.wassa-1.8/).

Languages

The BCP-47 code for the dataset's language is it.

Dataset Structure

Data Instances

@inproceedings{bianchi2021feel, title = {{"Sentiment Classification for the Italian Language"}}, author = "Bianchi, Federico and Nozza, Debora and Hovy, Dirk", booktitle = "Proceedings of the 11th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis", year = "2021", publisher = "Association for Computational Linguistics", }

Dataset Fields

The dataset has the following fields (also called "features"):

{
  "text": "Value(dtype='string', id=None)",
  "feat_id_noticia": "Value(dtype='int16', id=None)",
  "feat_target": "Value(dtype='string', id=None)",
  "target": "ClassLabel(names=['NEG', 'NEU', 'POS'], id=None)"
}

Dataset Splits

This dataset is split into a train and validation split. The split sizes are as follow:

Split name Num samples
train 1096
valid 275