Datasets:
offcombr

	# 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("'"),
	}