Datasets:
covid_tweets_japanese

	# 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.
	"""COVID-19 Japanese Tweets Dataset."""


	import bz2
	import csv

	import datasets


	_CITATION = """\
	No paper about this dataset is published yet. \
	Please cite this dataset as "鈴木優: COVID-19 日本語 Twitter データセット（http://www.db.info.gifu-u.ac.jp/covid-19-twitter-dataset/）"
	"""

	_DESCRIPTION = """\
	53,640 Japanese tweets with annotation if a tweet is related to COVID-19 or not. The annotation is by majority decision by 5 - 10 crowd workers. \
	Target tweets include "COVID" or "コロナ". The period of the tweets is from around January 2020 to around June 2020. \
	The original tweets are not contained. Please use Twitter API to get them, for example.
	"""

	_HOMEPAGE = "http://www.db.info.gifu-u.ac.jp/covid-19-twitter-dataset/"

	_LICENSE = "CC-BY-ND 4.0"

	# The HuggingFace dataset library don't host the datasets but only point to the original files
	# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
	_URLs = {
	"url": "http://www.db.info.gifu-u.ac.jp/data/covid19.csv.bz2",
	}


	class CovidTweetsJapanese(datasets.GeneratorBasedBuilder):
	"""COVID-19 Japanese Tweets Dataset."""

	VERSION = datasets.Version("1.1.0")

	def _info(self):
	features = datasets.Features(
	{
	"tweet_id": datasets.Value("string"),
	"assessment_option_id": datasets.ClassLabel(names=["63", "64", "65", "66", "67", "68"]),
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	supervised_keys=None,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""

	my_urls = _URLs["url"]
	# data_url = dl_manager.download_and_extract(my_urls)
	data_url = dl_manager.download(my_urls)

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={"filepath": data_url, "split": "train"},
	),
	]

	def _generate_examples(self, filepath, split):
	"""Yields examples."""

	with bz2.open(filepath, "rt") as f:
	data = csv.reader(f)
	_ = next(data)
	for id_, row in enumerate(data):
	yield id_, {
	"tweet_id": row[0],
	"assessment_option_id": row[1],
	}