Datasets:
Tasks:
Text Classification
Languages:
Portuguese
Size:
1K<n<10K
Tags:
hate-speech-detection
License:
File size: 3,516 Bytes
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# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""OffComBR: an annotated dataset containing for hate speech detection in Portuguese composed of news comments on the Brazilian Web."""
import datasets
_CITATION = """\
@article{Pelle2017,
title={Offensive Comments in the Brazilian Web: a dataset and baseline results},
author={Rogers P. de Pelle and Viviane P. Moreira},
booktitle={6th Brazilian Workshop on Social Network Analysis and Mining (BraSNAM)},
year={2017},
}
"""
_DESCRIPTION = """\
OffComBR: an annotated dataset containing for hate speech detection in Portuguese composed of news comments on the Brazilian Web.
"""
_HOMEPAGE = "http://www.inf.ufrgs.br/~rppelle/hatedetector/"
_LICENSE = "Unknown"
_URLs = {
"offcombr-2": "https://github.com/rogersdepelle/OffComBR/raw/master/OffComBR2.arff",
"offcombr-3": "https://github.com/rogersdepelle/OffComBR/raw/master/OffComBR3.arff",
}
class Offcombr(datasets.GeneratorBasedBuilder):
"""OffComBR: an annotated dataset containing for hate speech detection in Portuguese composed of news comments on the Brazilian Web."""
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="offcombr-2",
version=VERSION,
description="OffComBR-2 contains samples with Fleiss Kappa measure between annotators of 0.71",
),
datasets.BuilderConfig(
name="offcombr-3",
version=VERSION,
description="OffComBR-3 only contains instances for which the class has been agreed by all three judges",
),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"label": datasets.ClassLabel(names=["no", "yes"]),
"text": datasets.Value("string"),
}
),
supervised_keys=("label", "text"),
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
urls = _URLs[self.config.name]
data_file = dl_manager.download_and_extract(urls)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": data_file,
},
),
]
def _generate_examples(self, filepath):
"""Yields examples."""
with open(filepath, encoding="utf-8") as f:
for id_, row in enumerate(f):
if id_ < 8:
continue
label, *text = row.split(",")
text = "".join(text)
yield id_, {
"label": label,
"text": text.strip().strip("'"),
}
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