---
license: cc-by-sa-4.0
task_categories:
- text-classification
language:
- el
tags:
- code
size_categories:
- n<1K
---
# SentiMP-Gr Dataset
The SentiMP-Gr Dataset is a greek sentiment analysis dataset based on tweets written by members of parliament in United Kingdom in 2021. It has been developed collaboratively by the [Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI)](https://dasci.es/) research group from the [University of Granada](https://www.ugr.es/), the [SINAI](https://sinai.ujaen.es/) research group from the [University of Jaén](https://www.ujaen.es/) and the [Cardiff NLP](https://sites.google.com/view/cardiffnlp/) research group from the [University of Cardiff](https://isc.cardiff.ac.uk/).
## Dataset details
The dataset containst 500 tweets in Greek. For each tweet we provide the following information:
* **full_text**: Which containts the content of the tweet.
* **fold**: Proposed partitions \{0,1,2,3,4\} in 5 folds for 5 fold cross-validation for the sake of reproducibility.
* **label_i** : Annotator's i label (i in \{1,2,3\}). It takes values in \{-1,0,1\}.
* **majority_vote**: The result after applying the majority vote strategy to the annotators' partial labelling. When there is a tie we use the label "TIE". It takes values in \{-1,0,1,TIE\}.
* **tie_break**: We use this column to break ties in cases where there is a tie. Therefore, it is only completed when TIE appears in the *majority_vote* column. It takes values in \{-1,0,1\}.
* **gold_label**: It represents the final label. It is a combination between the *majority_vote* abd the *tie_break* columns. It takes values in \{-1,0,1\}.
## Citation
If you use this dataset, please cite:
## Contact
Nuria Rodríguez Barroso - rbnuria@ugr.es
## Acknowledgements
This work was partly supported by the grants PID2020-119478GB-I00, PID2020-116118GA-I00 and TED2021-130145B-I00 funded by MCIN/AEI/10.13039/501100011033 of the Spanish Government.
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