File size: 3,360 Bytes
83d24b2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 | from __future__ import annotations
from mteb.abstasks import AbsTaskClassification, MultilingualTask
from mteb.abstasks.TaskMetadata import TaskMetadata
_LANGS = {
"spanish": ["spa-Latn"],
"catalan": ["cat-Latn"],
}
class CataloniaTweetClassification(MultilingualTask, AbsTaskClassification):
metadata = TaskMetadata(
name="CataloniaTweetClassification",
description="""This dataset contains two corpora in Spanish and Catalan that consist of annotated Twitter
messages for automatic stance detection. The data was collected over 12 days during February and March
of 2019 from tweets posted in Barcelona, and during September of 2018 from tweets posted in the town of Terrassa, Catalonia.
Each corpus is annotated with three classes: AGAINST, FAVOR and NEUTRAL, which express the stance
towards the target - independence of Catalonia.
""",
reference="https://aclanthology.org/2020.lrec-1.171/",
dataset={
"path": "catalonia_independence",
"revision": "cf24d44e517efa534f048e5fc5981f399ed25bee",
},
type="Classification",
category="s2s",
eval_splits=["validation", "test"],
eval_langs=_LANGS,
main_score="accuracy",
date=("2018-09-01", "2029-03-30"),
form=["written"],
domains=["Social", "Government"],
task_subtypes=["Political classification"],
license="cc-by-sa-4.0",
socioeconomic_status="mixed",
annotations_creators="expert-annotated",
dialect=[],
text_creation="created",
bibtex_citation="""@inproceedings{zotova-etal-2020-multilingual,
title = "Multilingual Stance Detection in Tweets: The {C}atalonia Independence Corpus",
author = "Zotova, Elena and
Agerri, Rodrigo and
Nu{\~n}ez, Manuel and
Rigau, German",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
month = may,
year = "2020",
publisher = "European Language Resources Association",
pages = "1368--1375",
ISBN = "979-10-95546-34-4",
}""",
n_samples={"validation": 2000, "test": 2000},
avg_character_length={"validation": 202.61, "test": 200.49},
)
def dataset_transform(self):
for lang in self.dataset.keys():
self.dataset[lang] = self.dataset[lang].rename_columns(
{"TWEET": "text", "LABEL": "label"}
)
self.dataset[lang] = self.stratified_subsampling(
self.dataset[lang],
seed=self.seed,
splits=["validation", "test"],
n_samples=2000,
)
self.dataset[lang] = self.dataset[lang].remove_columns(["id_str"])
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