Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
fact-checking
Languages:
Bulgarian
Size:
1K - 10K
License:
Commit
•
116216d
1
Parent(s):
e8e75d2
Convert dataset to Parquet (#3)
Browse files- Convert dataset to Parquet (1978c528602a86a83e6bca25d7ef20709329b621)
- Delete loading script (919216c60d98865e14eeaa10c3dc6886b694a4c5)
- README.md +11 -4
- clickbait_news_bg.py +0 -119
- data/train-00000-of-00001.parquet +3 -0
- data/validation-00000-of-00001.parquet +3 -0
README.md
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@@ -42,13 +42,20 @@ dataset_info:
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dtype: string
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splits:
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- name: train
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num_bytes:
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num_examples: 2815
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- name: validation
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num_bytes:
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num_examples: 761
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download_size:
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dataset_size:
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---
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# Dataset Card for Clickbait/Fake News in Bulgarian
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dtype: string
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splits:
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- name: train
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num_bytes: 24480386
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num_examples: 2815
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- name: validation
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num_bytes: 6752226
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num_examples: 761
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download_size: 11831065
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dataset_size: 31232612
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: validation
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path: data/validation-*
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---
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# Dataset Card for Clickbait/Fake News in Bulgarian
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clickbait_news_bg.py
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# coding=utf-8
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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""" Dataset with clickbait and fake news in Bulgarian. """
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import openpyxl # noqa: requires this pandas optional dependency for reading xlsx files
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import pandas as pd
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import datasets
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_CITATION = """\
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@InProceedings{clickbait_news_bg,
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title = {Dataset with clickbait and fake news in Bulgarian. Introduced for the Hack the Fake News 2017.},
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authors={Data Science Society},
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year={2017},
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url={https://gitlab.com/datasciencesociety/case_fake_news/}
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}
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"""
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# TODO: Add description of the dataset here
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# You can copy an official description
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_DESCRIPTION = """\
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Dataset with clickbait and fake news in Bulgarian. Introduced for the Hack the Fake News 2017.
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"""
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# TODO: Add a link to an official homepage for the dataset here
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_HOMEPAGE = "https://gitlab.com/datasciencesociety/case_fake_news/"
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# TODO: Add the licence for the dataset here if you can find it
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_LICENSE = ""
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# TODO: Add link to the official dataset URLs here
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# The HuggingFace dataset library don't host the datasets but only point to the original files
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# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
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_URLs = {
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"default_train": "https://gitlab.com/datasciencesociety/case_fake_news/-/raw/master/data/FN_Training_Set.xlsx",
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"default_validation": "https://gitlab.com/datasciencesociety/case_fake_news/-/raw/master/data/FN_Validation_Set.xlsx",
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}
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class ClickbaitNewsBG(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version("1.1.0")
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DEFAULT_CONFIG_NAME = "default"
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def _info(self):
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if self.config.name == "default":
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features = datasets.Features(
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{
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"fake_news_score": datasets.features.ClassLabel(names=["legitimate", "fake"]),
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"click_bait_score": datasets.features.ClassLabel(names=["normal", "clickbait"]),
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"content_title": datasets.Value("string"),
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"content_url": datasets.Value("string"),
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"content_published_time": datasets.Value("string"),
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"content": datasets.Value("string"),
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}
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)
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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supervised_keys=None,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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data_dir = dl_manager.download(_URLs)
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return [
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datasets.SplitGenerator(
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name=spl_enum,
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gen_kwargs={
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"filepath": data_dir[f"{self.config.name}_{spl}"],
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"split": spl,
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},
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)
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for spl, spl_enum in [
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("train", datasets.Split.TRAIN),
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("validation", datasets.Split.VALIDATION),
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]
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]
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def _generate_examples(self, filepath, split):
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"""Yields examples."""
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keys = [
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"fake_news_score",
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"click_bait_score",
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"content_title",
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"content_url",
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"content_published_time",
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"content",
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]
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with open(filepath, "rb") as f:
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data = pd.read_excel(f, engine="openpyxl")
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for id_, row in enumerate(data.itertuples()):
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row_dict = dict()
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for key, value in zip(keys, row[1:]):
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if key == "fake_news_score":
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row_dict[key] = "legitimate" if value == 1 else "fake"
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elif key == "click_bait_score":
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row_dict[key] = "normal" if value == 1 else "clickbait"
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else:
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row_dict[key] = str(value)
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yield id_, row_dict
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data/train-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:3d6662718de9e679a3bce60784a126fc4ecb632b391325a6afa87bf677ba70dd
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size 9021963
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data/validation-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:294a967642e26b5f570c3f89f0490ac77d1ef26406025a6f09a0a80d7d629f6a
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size 2809102
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