Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
fact-checking
Languages:
Japanese
Size:
10K - 100K
License:
File size: 3,230 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.
"""COVID-19 Japanese Tweets Dataset."""
from __future__ import absolute_import, division, print_function
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/data/Data_5f02db873363f976fce930d1）"
"""
_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/data/Data_5f02db873363f976fce930d1"
_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/data.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],
}
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