Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

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README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- expert-generated
+languages:
+- id
+licenses:
+- cc-by-4-0
+multilinguality:
+- monolingual
+size_categories:
+- 10k>n>100k
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- fact-checking
+---
+
+# Dataset Card for Indonesian Clickbait Headlines
+
+## Table of Contents
+
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** [CLICK-ID: A Novel Dataset for Indonesian Clickbait Headlines](https://www.sciencedirect.com/science/article/pii/S2352340920311252#!)
+- **Repository:** [CLICK-ID: A Novel Dataset for Indonesian Clickbait Headlines](http://dx.doi.org/10.17632/k42j7x2kpn.1)
+- **Paper:** [CLICK-ID: A Novel Dataset for Indonesian Clickbait Headlines](https://www.sciencedirect.com/science/article/pii/S2352340920311252#!)
+- **Leaderboard:**
+- **Point of Contact:** [Andika William](mailto:andika.william@mail.ugm.ac.id), [Yunita Sari](mailto:yunita.sari@ugm.ac.id)
+
+### Dataset Summary
+
+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.
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+Indonesian
+
+## Dataset Structure
+### Data Instances
+An example of the annotated article:
+```
+{
+  'id': '100',
+  'label': 1,
+  'title': "SAH! Ini Daftar Nama Menteri Kabinet Jokowi - Ma'ruf Amin"
+}
+>
+``` 
+
+### Data Fields
+
+#### Annotated
+- `id`: id of the sample
+- `title`: the title of the news article
+- `label`: the label of the article, either non-clickbait or clickbait
+
+#### Raw
+- `id`: id of the sample
+- `title`: the title of the news article
+- `source`: the name of the publisher/newspaper
+- `date`: date
+- `category`: the category of the article
+- `sub-category`: the sub category of the article
+- `content`: the content of the article
+- `url`: the url of the article
+
+### Data Splits
+
+The dataset contains train set.
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+Creative Commons Attribution 4.0 International license
+
+### Citation Information
+```
+@article{WILLIAM2020106231,
+title = "CLICK-ID: A novel dataset for Indonesian clickbait headlines",
+journal = "Data in Brief",
+volume = "32",
+pages = "106231",
+year = "2020",
+issn = "2352-3409",
+doi = "https://doi.org/10.1016/j.dib.2020.106231",
+url = "http://www.sciencedirect.com/science/article/pii/S2352340920311252",
+author = "Andika William and Yunita Sari",
+keywords = "Indonesian, Natural Language Processing, News articles, Clickbait, Text-classification",
+abstract = "News analysis is a popular task in Natural Language Processing (NLP). In particular, the problem of clickbait in news analysis has gained attention in recent years [1, 2]. However, the majority of the tasks has been focused on English news, in which there is already a rich representative resource. For other languages, such as Indonesian, there is still a lack of resource for clickbait tasks. Therefore, we introduce the CLICK-ID dataset of Indonesian news headlines extracted from 12 Indonesian online news publishers. It is comprised of 15,000 annotated headlines with clickbait and non-clickbait labels. Using the CLICK-ID dataset, we then developed an Indonesian clickbait classification model achieving favourable performance. We believe that this corpus will be useful for replicable experiments in clickbait detection or other experiments in NLP areas."
+}
+```

dataset_infos.json

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+{"annotated": {"description": "The CLICK-ID dataset is a collection of Indonesian news headlines that was collected from 12 local online news\npublishers; detikNews, Fimela, Kapanlagi, Kompas, Liputan6, Okezone, Posmetro-Medan, Republika, Sindonews, Tempo,\nTribunnews, and Wowkeren. This dataset is comprised of mainly two parts; (i) 46,119 raw article data, and (ii)\n15,000 clickbait annotated sample headlines. Annotation was conducted with 3 annotator examining each headline.\nJudgment were based only on the headline. The majority then is considered as the ground truth. In the annotated\nsample, our annotation shows 6,290 clickbait and 8,710 non-clickbait.\n", "citation": "@inproceedings{id_clickbait,\n  author    = {Andika William, Yunita Sari},\n  title     = {CLICK-ID: A Novel Dataset for Indonesian Clickbait Headlines},\n  year      = {2020},\n  url       = {http://dx.doi.org/10.17632/k42j7x2kpn.1},\n}\n", "homepage": "https://github.com/feryandi/Dataset-Artikel", "license": "Creative Commons Attribution 4.0 International license", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["non-clickbait", "clickbait"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "id_clickbait", "config_name": "annotated", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1268698, "num_examples": 15000, "dataset_name": "id_clickbait"}}, "download_checksums": {"https://md-datasets-cache-zipfiles-prod.s3.eu-west-1.amazonaws.com/k42j7x2kpn-1.zip": {"num_bytes": 150769127, "checksum": "42a2607d38422630e100165eb1bf120b16191798993cd5d04bfedf768bb2bd50"}}, "download_size": 150769127, "post_processing_size": null, "dataset_size": 1268698, "size_in_bytes": 152037825}, "raw": {"description": "The CLICK-ID dataset is a collection of Indonesian news headlines that was collected from 12 local online news\npublishers; detikNews, Fimela, Kapanlagi, Kompas, Liputan6, Okezone, Posmetro-Medan, Republika, Sindonews, Tempo,\nTribunnews, and Wowkeren. This dataset is comprised of mainly two parts; (i) 46,119 raw article data, and (ii)\n15,000 clickbait annotated sample headlines. Annotation was conducted with 3 annotator examining each headline.\nJudgment were based only on the headline. The majority then is considered as the ground truth. In the annotated\nsample, our annotation shows 6,290 clickbait and 8,710 non-clickbait.\n", "citation": "@inproceedings{id_clickbait,\n  author    = {Andika William, Yunita Sari},\n  title     = {CLICK-ID: A Novel Dataset for Indonesian Clickbait Headlines},\n  year      = {2020},\n  url       = {http://dx.doi.org/10.17632/k42j7x2kpn.1},\n}\n", "homepage": "https://github.com/feryandi/Dataset-Artikel", "license": "Creative Commons Attribution 4.0 International license", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "source": {"dtype": "string", "id": null, "_type": "Value"}, "date": {"dtype": "string", "id": null, "_type": "Value"}, "category": {"dtype": "string", "id": null, "_type": "Value"}, "sub-category": {"dtype": "string", "id": null, "_type": "Value"}, "content": {"dtype": "string", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "id_clickbait", "config_name": "raw", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 81669386, "num_examples": 38655, "dataset_name": "id_clickbait"}}, "download_checksums": {"https://md-datasets-cache-zipfiles-prod.s3.eu-west-1.amazonaws.com/k42j7x2kpn-1.zip": {"num_bytes": 150769127, "checksum": "42a2607d38422630e100165eb1bf120b16191798993cd5d04bfedf768bb2bd50"}}, "download_size": 150769127, "post_processing_size": null, "dataset_size": 81669386, "size_in_bytes": 232438513}}

dummy/annotated/1.0.0/dummy_data.zip

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+size 1539

dummy/raw/1.0.0/dummy_data.zip

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id_clickbait.py

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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.
+"""CLICK-ID: A Novel Dataset for Indonesian Clickbait Headlines"""
+
+from __future__ import absolute_import, division, print_function
+
+import csv
+import glob
+import logging
+import os
+
+import datasets
+
+
+_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://github.com/feryandi/Dataset-Artikel"
+
+_LICENSE = "Creative Commons Attribution 4.0 International license"
+
+_URLs = ["https://md-datasets-cache-zipfiles-prod.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="annotated/csv",
+        ),
+        IdClickbaitConfig(name="raw", version=VERSION, description="Raw dataset", path="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):
+        my_urls = _URLs[0]
+        data_dir = dl_manager.download_and_extract(my_urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "article_dir": os.path.join(data_dir, self.config.path),
+                    "split": "train",
+                },
+            )
+        ]
+
+    def _generate_examples(self, article_dir, split):
+        logging.info("⏳ Generating %s examples from = %s", split, article_dir)
+        id = 0
+        for path in sorted(glob.glob(os.path.join(article_dir, "**/*.csv"), recursive=True)):
+            with open(path, encoding="utf-8-sig", newline="") as f:
+                reader = csv.DictReader(f)
+                for row in reader:
+                    if self.config.name == "annotated":
+                        yield id, {
+                            "id": str(id),
+                            "title": row["title"],
+                            "label": row["label"],
+                        }
+                    else:
+                        yield id, {
+                            "id": str(id),
+                            "title": row["title"],
+                            "source": row["source"],
+                            "date": row["date"],
+                            "category": row["category"],
+                            "sub-category": row["sub-category"],
+                            "content": row["content"],
+                            "url": row["url"],
+                        }
+                    id += 1