add reader, dataset, metadata, documentation

README.md

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+---
+annotations_creators:
+- expert_generated
+language_creators:
+- found
+languages:
+- sq-AL
+licenses:
+- cc-by-4.0
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- text_classification
+task_ids:
+- hate-speech-detection
+paperswithcode_id: 
+pretty_name: SHAJ
+extra_gated_prompt: "Warning: this repository contains harmful content (abusive language, hate speech)."
+---
+
+# Dataset Card for "shaj"
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [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)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** 
+- **Repository:** [https://figshare.com/articles/dataset/SHAJ_Albanian_hate_speech_abusive_language/19333298/1](https://figshare.com/articles/dataset/SHAJ_Albanian_hate_speech_abusive_language/19333298/1)
+- **Paper:** [https://arxiv.org/abs/2107.13592](https://arxiv.org/abs/2107.13592)
+- **Point of Contact:** [Leon Derczynski](https://github.com/leondz)
+- **Size of downloaded dataset files:** 769.21 KiB
+- **Size of the generated dataset:** 1.06 MiB
+- **Total amount of disk used:**  1.85 MiB
+
+### Dataset Summary
+
+This is an abusive/offensive language detection dataset for Albanian. The data is formatted
+following the OffensEval convention, with three tasks:
+
+* Subtask A: Offensive (OFF) or not (NOT)
+* Subtask B: Untargeted (UNT) or targeted insult (TIN)
+* Subtask C: Type of target: individual (IND), group (GRP), or other (OTH)
+
+* The subtask A field should always be filled.
+* The subtask B field should only be filled if there's "offensive" (OFF) in A.
+* The subtask C field should only be filled if there's "targeted" (TIN) in B.
+
+The dataset name is a backronym, also standing for "Spoken Hate in the Albanian Jargon"
+
+See the paper [https://arxiv.org/abs/2107.13592](https://arxiv.org/abs/2107.13592) for full details.
+
+### Supported Tasks and Leaderboards
+
+* 
+
+### Languages
+
+Albanian (`bcp47:sq-AL`)
+
+## Dataset Structure
+
+### Data Instances
+
+#### shaj
+
+- **Size of downloaded dataset files:** 769.21 KiB
+- **Size of the generated dataset:** 1.06 MiB
+- **Total amount of disk used:**  1.85 MiB
+
+An example of 'train' looks as follows.
+
+```
+{
+  'id': '0', 
+  'text': 'PLACEHOLDER TEXT', 
+  'subtask_a': 1, 
+  'subtask_b': 0, 
+  'subtask_c': 0
+}
+```
+
+
+### Data Fields
+
+- `id`: a `string` feature.
+- `text`: a `string`.
+- `subtask_a`: whether or not the instance is offensive; `0: OFF, 1: NOT`
+- `subtask_b`: whether an offensive instance is a targeted insult; `0: TIN, 1: UNT, 2: not applicable`
+- `subtask_c`: what a targeted insult is aimed at; `0: IND, 1: GRP, 2: OTH, 3: not applicable`
+
+
+### Data Splits
+
+|  name   |train|
+|---------|----:|
+|shaj|11874 sentences|
+
+## Dataset Creation
+
+### Curation Rationale
+
+Collecting data for enabling offensive speech detection in Albanian
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+The text is scraped from comments on popular Albanian YouTube and Instagram accounts.
+An extended discussion is given in the paper in section 3.2.
+
+#### Who are the source language producers?
+
+Russian speakers including from the Russian diaspora, especially Latvia
+
+### Annotations
+
+#### Annotation process
+
+The annotation scheme was taken from OffensEval 2019 and applied by two native speaker authors of the paper as well as their friends and family.
+
+#### Who are the annotators?
+
+Albanian native speakers, male and female, aged 20-60.
+
+### Personal and Sensitive Information
+
+The data was public at the time of collection. No PII removal has been performed.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+The data definitely contains abusive language.
+
+### Discussion of Biases
+
+
+### Other Known Limitations
+
+
+## Additional Information
+
+### Dataset Curators
+
+The dataset is curated by the paper's authors.
+
+### Licensing Information
+
+The authors distribute this data under Creative Commons attribution license, CC-BY 4.0. 
+
+### Citation Information
+
+```
+@article{nurce2021detecting,
+  title={Detecting Abusive Albanian},
+  author={Nurce, Erida and Keci, Jorgel and Derczynski, Leon},
+  journal={arXiv preprint arXiv:2107.13592},
+  year={2021}
+}
+```
+
+
+### Contributions
+
+Author-added dataset [@leondz](https://github.com/leondz) 

dataset_infos.json

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+{"Shaj": {"description": "This is an abusive/offensive language detection dataset for Albanian. The data is formatted\nfollowing the OffensEval convention, with three tasks:\n\n* Subtask A: Offensive (OFF) or not (NOT)\n* Subtask B: Untargeted (UNT) or targeted insult (TIN)\n* Subtask C: Type of target: individual (IND), group (GRP), or other (OTH)\n\n* The subtask A field should always be filled.\n* The subtask B field should only be filled if there's \"offensive\" (OFF) in A.\n* The subtask C field should only be filled if there's \"targeted\" (TIN) in B.\n\nThe dataset name is a backronym, also standing for \"Spoken Hate in the Albanian Jargon\"\n\nSee the paper [https://arxiv.org/abs/2107.13592](https://arxiv.org/abs/2107.13592) for full details.\n", "citation": "@article{nurce2021detecting,\n  title={Detecting Abusive Albanian},\n  author={Nurce, Erida and Keci, Jorgel and Derczynski, Leon},\n  journal={arXiv preprint arXiv:2107.13592},\n  year={2021}\n}\n", "homepage": "https://arxiv.org/abs/2107.13592", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "subtask_a": {"num_classes": 2, "names": ["OFF", "NOT"], "id": null, "_type": "ClassLabel"}, "subtask_b": {"num_classes": 3, "names": ["", "TIN", "UNT"], "id": null, "_type": "ClassLabel"}, "subtask_c": {"num_classes": 4, "names": ["", "IND", "GRP", "OTH"], "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "shaj", "config_name": "Shaj", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1116165, "num_examples": 11875, "dataset_name": "shaj"}}, "download_checksums": {"full_albanian_dataset.csv": {"num_bytes": 787673, "checksum": "128cd9915b723a8202f94eda129e82c5d75fb9a1c8dbbe48d0092bb633c3bc3c"}}, "download_size": 787673, "post_processing_size": null, "dataset_size": 1116165, "size_in_bytes": 1903838}}

shaj.py

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+# coding=utf-8
+# Copyright 2020 HuggingFace Datasets Authors.
+#
+# 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.
+
+# Lint as: python3
+"""SHAJ: An abusive language dataset for Albanian"""
+
+import csv
+import os
+
+import datasets
+
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_CITATION = """\
+@article{nurce2021detecting,
+  title={Detecting Abusive Albanian},
+  author={Nurce, Erida and Keci, Jorgel and Derczynski, Leon},
+  journal={arXiv preprint arXiv:2107.13592},
+  year={2021}
+}
+"""
+
+_DESCRIPTION = """\
+This is an abusive/offensive language detection dataset for Albanian. The data is formatted
+following the OffensEval convention, with three tasks:
+
+* Subtask A: Offensive (OFF) or not (NOT)
+* Subtask B: Untargeted (UNT) or targeted insult (TIN)
+* Subtask C: Type of target: individual (IND), group (GRP), or other (OTH)
+
+* The subtask A field should always be filled.
+* The subtask B field should only be filled if there's "offensive" (OFF) in A.
+* The subtask C field should only be filled if there's "targeted" (TIN) in B.
+
+The dataset name is a backronym, also standing for "Spoken Hate in the Albanian Jargon"
+
+See the paper [https://arxiv.org/abs/2107.13592](https://arxiv.org/abs/2107.13592) for full details.
+"""
+
+_URL = "full_albanian_dataset.csv"
+
+
+class ShajConfig(datasets.BuilderConfig):
+    """BuilderConfig for Shaj"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig Shaj.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(ShajConfig, self).__init__(**kwargs)
+
+
+class Shaj(datasets.GeneratorBasedBuilder):
+    """Shaj dataset."""
+
+    BUILDER_CONFIGS = [
+        ShajConfig(name="Shaj", version=datasets.Version("1.0.0"), description="Abusive language dataset in Albanian"),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                    "subtask_a": datasets.features.ClassLabel(
+                        names=[
+                            "OFF",
+                            "NOT",
+                        ]
+                    ),
+                    "subtask_b": datasets.features.ClassLabel(
+                        names=[
+                            "TIN",
+                            "UNT",
+                            "",
+                        ]
+                    ),
+                    "subtask_c": datasets.features.ClassLabel(
+                        names=[
+                            "IND",
+                            "GRP",
+                            "OTH",
+                            "",
+                        ]
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://arxiv.org/abs/2107.13592",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        downloaded_file = dl_manager.download_and_extract(_URL)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file}),
+        ]
+
+    def _generate_examples(self, filepath):
+        logger.info("⏳ Generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            shaj_reader = csv.DictReader(f, fieldnames=('text','subtask_a','subtask_b','subtask_c'), delimiter=";", quotechar='"')
+            guid = 0
+            for instance in shaj_reader:
+                instance["id"] = str(guid)
+                yield guid, instance
+                guid += 1