Datasets:
Tasks:
Text Classification
Sub-tasks:
fact-checking
Languages:
Indonesian
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
expert-generated
Annotations Creators:
expert-generated
Source Datasets:
original
License:
# 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. | |
"""CLICK-ID: A Novel Dataset for Indonesian Clickbait Headlines""" | |
import csv | |
import glob | |
import os | |
import datasets | |
logger = datasets.logging.get_logger(__name__) | |
_CITATION = """\ | |
@inproceedings{id_clickbait, | |
author = {Andika William, Yunita Sari}, | |
title = {CLICK-ID: A Novel Dataset for Indonesian Clickbait Headlines}, | |
year = {2020}, | |
url = {http://dx.doi.org/10.17632/k42j7x2kpn.1}, | |
} | |
""" | |
_DESCRIPTION = """\ | |
The CLICK-ID dataset is a collection of Indonesian news headlines that was collected from 12 local online news | |
publishers; detikNews, Fimela, Kapanlagi, Kompas, Liputan6, Okezone, Posmetro-Medan, Republika, Sindonews, Tempo, | |
Tribunnews, and Wowkeren. This dataset is comprised of mainly two parts; (i) 46,119 raw article data, and (ii) | |
15,000 clickbait annotated sample headlines. Annotation was conducted with 3 annotator examining each headline. | |
Judgment were based only on the headline. The majority then is considered as the ground truth. In the annotated | |
sample, our annotation shows 6,290 clickbait and 8,710 non-clickbait. | |
""" | |
_HOMEPAGE = "https://data.mendeley.com/datasets/k42j7x2kpn/1" | |
_LICENSE = "Creative Commons Attribution 4.0 International license" | |
_URL = "https://prod-dcd-datasets-cache-zipfiles.s3.eu-west-1.amazonaws.com/k42j7x2kpn-1.zip" | |
class IdClickbaitConfig(datasets.BuilderConfig): | |
"""BuilderConfig for IdClickbait""" | |
def __init__(self, label_classes=None, path=None, **kwargs): | |
"""BuilderConfig for IdClickbait. | |
Args: | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super(IdClickbaitConfig, self).__init__(**kwargs) | |
self.label_classes = label_classes | |
self.path = path | |
class IdClickbait(datasets.GeneratorBasedBuilder): | |
VERSION = datasets.Version("1.0.0") | |
BUILDER_CONFIGS = [ | |
IdClickbaitConfig( | |
name="annotated", | |
version=VERSION, | |
description="Annotated clickbait dataset", | |
label_classes=["non-clickbait", "clickbait"], | |
path=os.path.join("annotated", "csv"), | |
), | |
IdClickbaitConfig(name="raw", version=VERSION, description="Raw dataset", path=os.path.join("raw", "csv")), | |
] | |
BUILDER_CONFIG_CLASS = IdClickbaitConfig | |
def _info(self): | |
if self.config.name == "annotated": | |
features = datasets.Features( | |
{ | |
"id": datasets.Value("string"), | |
"title": datasets.Value("string"), | |
"label": datasets.features.ClassLabel(names=self.config.label_classes), | |
} | |
) | |
else: | |
features = datasets.Features( | |
{ | |
"id": datasets.Value("string"), | |
"title": datasets.Value("string"), | |
"source": datasets.Value("string"), | |
"date": datasets.Value("string"), | |
"category": datasets.Value("string"), | |
"sub-category": datasets.Value("string"), | |
"content": datasets.Value("string"), | |
"url": datasets.Value("string"), | |
} | |
) | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=features, | |
supervised_keys=None, | |
homepage=_HOMEPAGE, | |
license=_LICENSE, | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
data_dir = dl_manager.download_and_extract(_URL) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={ | |
"article_dir": os.path.join(data_dir, self.config.path), | |
}, | |
) | |
] | |
def _generate_examples(self, article_dir): | |
logger.info(f"⏳ Generating examples from = {article_dir}") | |
idx = 0 | |
for path in sorted(glob.glob(os.path.join(article_dir, "*.csv"))): | |
with open(path, encoding="utf-8-sig", newline="") as f: | |
reader = csv.DictReader(f) | |
for row in reader: | |
if self.config.name == "annotated": | |
yield idx, { | |
"id": str(idx), | |
"title": row["title"], | |
"label": row["label"], | |
} | |
else: | |
yield idx, { | |
"id": str(idx), | |
"title": row["title"], | |
"source": row["source"], | |
"date": row["date"], | |
"category": row["category"], | |
"sub-category": row["sub-category"], | |
"content": row["content"], | |
"url": row["url"], | |
} | |
idx += 1 | |