|
--- |
|
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"): |
|
|
|
```json |
|
{ |
|
"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 | |
