Datasets:
urdu_fake_news

	"""Urdu Fake News Dataset"""


	import glob
	import os

	import datasets


	_CITATION = """
	@article{MaazUrdufake2020,
	author = {Amjad, Maaz and Sidorov, Grigori and Zhila, Alisa and G’{o}mez-Adorno, Helena and Voronkov, Ilia and Gelbukh, Alexander},
	title = {Bend the Truth: A Benchmark Dataset for Fake News Detection in Urdu and Its Evaluation},
	journal={Journal of Intelligent & Fuzzy Systems},
	volume={39},
	number={2},
	pages={2457-2469},
	doi = {10.3233/JIFS-179905},
	year={2020},
	publisher={IOS Press}
	}
	"""

	_DESCRIPTION = """
	Urdu fake news datasets that contain news of 5 different news domains.
	These domains are Sports, Health, Technology, Entertainment, and Business.
	The real news are collected by combining manual approaches.
	"""

	_URL = "https://github.com/MaazAmjad/Datasets-for-Urdu-news/blob/master/"
	_URL += "Urdu%20Fake%20News%20Dataset.zip?raw=true"


	class UrduFakeNews(datasets.GeneratorBasedBuilder):
	VERSION = datasets.Version("1.0.0")

	category_list = [
	"bus",
	"hlth",
	"sp",
	"tch",
	"sbz",
	]

	def _info(self):
	labels_list = ["Fake", "Real"]

	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"news": datasets.Value("string"),
	"label": datasets.ClassLabel(names=labels_list),
	"category": datasets.ClassLabel(names=self.category_list),
	}
	),
	homepage="https://github.com/MaazAmjad/Datasets-for-Urdu-news",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	dl_path = dl_manager.download_and_extract(_URL)
	input_path = os.path.join(dl_path, "1.Corpus")
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={"pattern": os.path.join(input_path, "Train", "", ".txt")},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={"pattern": os.path.join(input_path, "Test", "", ".txt")},
	),
	]

	def _generate_examples(self, pattern=None):
	"""Yields examples."""
	for filename in sorted(glob.glob(pattern)):

	with open(filename, encoding="utf-8") as f:
	news = ""
	for line in f:
	if line == "\n":
	continue
	news += line

	name = os.path.basename(filename)
	key = name.rstrip(".txt")

	_class = 1 if ("Real" in filename) else 0
	_class_name = "Real" if ("Real" in filename) else "Fake"
	category = "".join([i for i in key if not i.isdigit()])
	if category == "":
	continue
	category = self.category_list.index(category)

	yield f"{_class_name}_{key}", {"news": news, "label": _class, "category": category}