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:
+- crowdsourced
+- expert-generated
+language_creators:
+- found, other
+languages:
+- en
+licenses:
+- agpl-3-0-or-later
+multilinguality:
+- monolingual
+size_categories:
+- n<1K
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+  binary:
+  - sentiment-classification
+  - text-classification-other-Hate Speech Detection
+  multilabel:
+  - multi-label-classification
+  - sentiment-classification
+  - text-classification-other-Hate Speech Detection
+---
+
+# Dataset Card for Ethos
+
+## 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-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)
+
+## Dataset Description
+
+- **Homepage:** [ETHOS Hate Speech Dataset](https://github.com/intelligence-csd-auth-gr/Ethos-Hate-Speech-Dataset)
+- **Repository:**[ETHOS Hate Speech Dataset](https://github.com/intelligence-csd-auth-gr/Ethos-Hate-Speech-Dataset)
+- **Paper:**[ETHOS: an Online Hate Speech Detection Dataset](https://arxiv.org/abs/2006.08328)
+
+### Dataset Summary
+
+ETHOS: onlinE haTe speecH detectiOn dataSet. This repository contains a dataset for hate speech detection on social media platforms, called Ethos. There are two variations of the dataset:
+- **Ethos_Dataset_Binary**: contains 998 comments in the dataset alongside with a label about hate speech *presence* or *absence*. 565 of them do not contain hate speech, while the rest of them, 433, contain. 
+- **Ethos_Dataset_Multi_Label** which contains 8 labels for the 433 comments with hate speech content. These labels are *violence* (if it incites (1) or not (0) violence), *directed_vs_general* (if it is directed to a person (1) or a group (0)), and 6 labels about the category of hate speech like, *gender*, *race*, *national_origin*, *disability*, *religion* and *sexual_orientation*.
+
+***Ethos /ˈiːθɒs/*** 
+is a Greek word meaning “character” that is used to describe the guiding beliefs or ideals that characterize a community, nation, or ideology. The Greeks also used this word to refer to the power of music to influence emotions, behaviors, and even morals.
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+- `text-classification-other-Hate Speech Detection`, `sentiment-classification`,`multi-label-classification`: The dataset can be used to train a model for hate speech detection. Moreover, it can be used as a benchmark dataset for multi label classification algorithms.
+
+### Languages
+
+The text in the dataset is in English.
+
+## Dataset Structure
+
+### Data Instances
+
+A typical data point in the binary version comprises a comment, with a `text` containing the  text and a `label` describing if a comment contains hate speech content (1 - hate-speech) or not (0 - non-hate-speech). In the multilabel version more labels like *violence* (if it incites (1) or not (0) violence), *directed_vs_general* (if it is directed to a person (1) or a group (0)), and 6 labels about the category of hate speech like, *gender*, *race*, *national_origin*, *disability*, *religion* and *sexual_orientation* are appearing.
+
+An example from the binary version, which is offensive, but it does not contain hate speech content:
+```
+{'text': 'What the fuck stupid people !!!',
+ 'label': '0'
+}
+```
+
+An example from the multi-label version, which contains hate speech content towards women (gender):
+```
+{'text': 'You should know women's sports are a joke',
+ `violence`: 0,
+ `directed_vs_generalized`: 0,
+ `gender`: 1,
+ `race`: 0,
+ `national_origin`: 0,
+ `disability`: 0,
+ `religion`: 0,
+ `sexual_orientation`: 0
+}
+```
+
+
+### Data Fields
+
+Ethos Binary:
+- `text`: a `string` feature containing the text of the comment.
+- `label`: a classification label, with possible values including `no_hate_speech`, `hate_speech`.
+
+Ethis Multilabel:
+- `text`: a `string` feature containing the text of the comment.
+- `violence`: a classification label, with possible values including `not_violent`, `violent`.
+- `directed_vs_generalized`: a classification label, with possible values including `generalized`, `directed`.
+- `gender`: a classification label, with possible values including `false`, `true`.
+- `race`: a classification label, with possible values including `false`, `true`.
+- `national_origin`: a classification label, with possible values including `false`, `true`.
+- `disability`: a classification label, with possible values including `false`, `true`.
+- `religion`: a classification label, with possible values including `false`, `true`.
+- `sexual_orientation`: a classification label, with possible values including `false`, `true`.
+
+### Data Splits
+
+The data is split into binary and multilabel. Multilabel is a subset of the binary version.
+
+|                             | Instances   | Labels |
+| -----                       | ------ | ----- |
+| binary | 998 |  1 |
+| multilabel       | 433 |  8 |
+
+## Dataset Creation
+
+### Curation Rationale
+
+The dataset was build by gathering online comments in Youtube videos and reddit comments, from videos and subreddits which may attract hate speech content. 
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+The initial data we used are from the hatebusters platform: [Original data used](https://intelligence.csd.auth.gr/topics/hate-speech-detection/), but they were not included in this dataset
+
+#### Who are the source language producers?
+
+The language producers are users of reddit and Youtube. More informations can be found in this paper: [ETHOS: an Online Hate Speech Detection Dataset](https://arxiv.org/abs/2006.08328)
+
+### Annotations
+
+#### Annotation process
+
+The annotation process is detailed in the third section of this paper: [ETHOS: an Online Hate Speech Detection Dataset](https://arxiv.org/abs/2006.08328)
+
+#### Who are the annotators?
+
+Originally anotated by Ioannis Mollas and validated through the Figure8 platform (APEN).
+
+### Personal and Sensitive Information
+
+No personal and sensitive information included in the dataset.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+This dataset will help on the evolution of the automated hate speech detection tools. Those tools have great impact on preventing social issues.
+
+### Discussion of Biases
+
+This dataset tries to be unbiased towards its classes and labels.
+
+### Other Known Limitations
+
+The dataset is relatively small and should be used combined with larger datasets.
+
+## Additional Information
+
+### Dataset Curators
+
+The dataset was initially created by [Intelligent Systems Lab](https://intelligence.csd.auth.gr).
+
+### Licensing Information
+
+The licensing status of the datasets is [GNU GPLv3](https://choosealicense.com/licenses/gpl-3.0/).
+
+### Citation Information
+```
+@misc{mollas2020ethos,
+      title={ETHOS: an Online Hate Speech Detection Dataset}, 
+      author={Ioannis Mollas and Zoe Chrysopoulou and Stamatis Karlos and Grigorios Tsoumakas},
+      year={2020},
+      eprint={2006.08328},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+
+## License
+[GNU GPLv3](https://choosealicense.com/licenses/gpl-3.0/)

dataset_infos.json

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+{"binary": {"description": "", "citation": "\n@misc{mollas2020ethos,\n      title={ETHOS: an Online Hate Speech Detection Dataset},\n      author={Ioannis Mollas and Zoe Chrysopoulou and Stamatis Karlos and Grigorios Tsoumakas},\n      year={2020},\n      eprint={2006.08328},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n ", "homepage": "https://github.com/intelligence-csd-auth-gr/Ethos-Hate-Speech-Dataset/tree/masterethos/ethos_data", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["no_hate_speech", "hate_speech"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "ethos", "config_name": "binary", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 124823, "num_examples": 998, "dataset_name": "ethos"}}, "download_checksums": {"https://raw.githubusercontent.com/intelligence-csd-auth-gr/Ethos-Hate-Speech-Dataset/master/ethos/ethos_data/Ethos_Dataset_Binary.csv": {"num_bytes": 123919, "checksum": "0cd0050c2592afcb5eca5876df485ca15cda9d7d16fe32c269857260fd10d96c"}}, "download_size": 123919, "post_processing_size": null, "dataset_size": 124823, "size_in_bytes": 248742}, "multilabel": {"description": "", "citation": "\n@misc{mollas2020ethos,\n      title={ETHOS: an Online Hate Speech Detection Dataset},\n      author={Ioannis Mollas and Zoe Chrysopoulou and Stamatis Karlos and Grigorios Tsoumakas},\n      year={2020},\n      eprint={2006.08328},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n ", "homepage": "https://github.com/intelligence-csd-auth-gr/Ethos-Hate-Speech-Dataset/tree/masterethos/ethos_data", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "violence": {"num_classes": 2, "names": ["not_violent", "violent"], "names_file": null, "id": null, "_type": "ClassLabel"}, "directed_vs_generalized": {"num_classes": 2, "names": ["generalied", "directed"], "names_file": null, "id": null, "_type": "ClassLabel"}, "gender": {"num_classes": 2, "names": ["false", "true"], "names_file": null, "id": null, "_type": "ClassLabel"}, "race": {"num_classes": 2, "names": ["false", "true"], "names_file": null, "id": null, "_type": "ClassLabel"}, "national_origin": {"num_classes": 2, "names": ["false", "true"], "names_file": null, "id": null, "_type": "ClassLabel"}, "disability": {"num_classes": 2, "names": ["false", "true"], "names_file": null, "id": null, "_type": "ClassLabel"}, "religion": {"num_classes": 2, "names": ["false", "true"], "names_file": null, "id": null, "_type": "ClassLabel"}, "sexual_orientation": {"num_classes": 2, "names": ["false", "true"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "ethos", "config_name": "multilabel", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 79112, "num_examples": 433, "dataset_name": "ethos"}}, "download_checksums": {"https://raw.githubusercontent.com/intelligence-csd-auth-gr/Ethos-Hate-Speech-Dataset/master/ethos/ethos_data/Ethos_Dataset_Multi_Label.csv": {"num_bytes": 62836, "checksum": "488c72a1582abdaf489a6e9eceeebba505447a00a25bd02e72fd6a56f9a3d83d"}}, "download_size": 62836, "post_processing_size": null, "dataset_size": 79112, "size_in_bytes": 141948}}

dummy/binary/1.0.0/dummy_data.zip

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dummy/multilabel/1.0.0/dummy_data.zip

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ethos.py

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+"""Ethos  dataset"""
+
+from __future__ import absolute_import, division, print_function
+
+import logging
+
+import pandas as pd
+
+import datasets
+
+
+_CITATION = """
+@misc{mollas2020ethos,
+      title={ETHOS: an Online Hate Speech Detection Dataset},
+      author={Ioannis Mollas and Zoe Chrysopoulou and Stamatis Karlos and Grigorios Tsoumakas},
+      year={2020},
+      eprint={2006.08328},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+ """
+
+_DESCRIPTION = """
+
+ETHOS: onlinE haTe speecH detectiOn dataSet. This repository contains a dataset for hate speech
+detection on social media platforms, called Ethos. There are two variations of the dataset:
+
+Ethos_Dataset_Binary: contains 998 comments in the dataset alongside with a label
+about hate speech presence or absence. 565 of them do not contain hate speech,
+while the rest of them, 433, contain.
+
+Ethos_Dataset_Multi_Label: which contains 8 labels for the 433 comments with hate speech content.
+These labels are violence (if it incites (1) or not (0) violence), directed_vs_general (if it is
+directed to a person (1) or a group (0)), and 6 labels about the category of hate speech like,
+gender, race, national_origin, disability, religion and sexual_orientation.
+"""
+
+_URL = "https://github.com/intelligence-csd-auth-gr/Ethos-Hate-Speech-Dataset"
+
+
+class EthosConfig(datasets.BuilderConfig):
+    """BuilderConfig for Ethos."""
+
+    def __init__(self, variation="binary", **kwargs):
+        """Constructs an EthosDataset.
+
+        Args:
+        variation: can be binary or multilabel
+        **kwargs: keyword arguments forwarded to super.
+        """
+        if variation.lower() == "binary":
+            self.variation = "binary"
+        elif variation.lower() == "multilabel":
+            self.variation = "multilabel"
+        else:
+            logging.warning("Wrong variation. Could be either 'binary' or 'multilabel', using 'binary' instead.")
+            self.variation = "binary"
+        super(EthosConfig, self).__init__(**kwargs)
+
+
+class Ethos(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIG_CLASS = EthosConfig
+
+    BUILDER_CONFIGS = [
+        EthosConfig(
+            name="binary",
+            version=datasets.Version("1.0.0", ""),
+            description="Ethos Binary",
+            variation="binary",
+        ),
+        EthosConfig(
+            name="multilabel",
+            version=datasets.Version("1.0.0", ""),
+            description="Ethos Multi Label",
+            variation="multilabel",
+        ),
+    ]
+
+    def _info(self):
+        if self.config.variation == "binary":
+            f = datasets.Features(
+                {
+                    "text": datasets.Value("string"),
+                    "label": datasets.features.ClassLabel(names=["no_hate_speech", "hate_speech"]),
+                }
+            )
+        else:
+            f = datasets.Features(
+                {
+                    "text": datasets.Value("string"),
+                    "violence": datasets.ClassLabel(names=["not_violent", "violent"]),
+                    "directed_vs_generalized": datasets.ClassLabel(names=["generalied", "directed"]),
+                    "gender": datasets.ClassLabel(names=["false", "true"]),
+                    "race": datasets.ClassLabel(names=["false", "true"]),
+                    "national_origin": datasets.ClassLabel(names=["false", "true"]),
+                    "disability": datasets.ClassLabel(names=["false", "true"]),
+                    "religion": datasets.ClassLabel(names=["false", "true"]),
+                    "sexual_orientation": datasets.ClassLabel(names=["false", "true"]),
+                }
+            )
+        return datasets.DatasetInfo(
+            features=f,
+            supervised_keys=None,
+            homepage="https://github.com/intelligence-csd-auth-gr/Ethos-Hate-Speech-Dataset/tree/masterethos/ethos_data",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        if self.config.variation == "binary":
+            url = {
+                "train": "https://raw.githubusercontent.com/intelligence-csd-auth-gr/Ethos-Hate-Speech-Dataset"
+                "/master/ethos/ethos_data/Ethos_Dataset_Binary.csv"
+            }
+        else:
+            url = {
+                "train": "https://raw.githubusercontent.com/intelligence-csd-auth-gr/Ethos-Hate-Speech-Dataset"
+                "/master/ethos/ethos_data/Ethos_Dataset_Multi_Label.csv"
+            }
+        downloaded_files = dl_manager.download_and_extract(url)
+
+        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]})]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+
+        data = pd.read_csv(filepath, delimiter=";")
+        if self.config.variation == "binary":
+
+            x = data["comment"].values
+            y = [1 if i >= 0.5 else 0 for i in data["isHate"].values]
+            class_names = ["no_hate_speech", "hate_speech"]
+            for i in range(len(x)):
+                _id = i
+                yield _id, {"text": x[i], "label": class_names[y[i]]}
+        else:
+            x = data["comment"].values
+            y_temp = data.loc[:, data.columns != "comment"].values
+            y = []
+            for yt in y_temp:
+                yi = []
+                for i in yt:
+                    if i >= 0.5:
+                        yi.append(int(1))
+                    else:
+                        yi.append(int(0))
+                y.append(yi)
+            for i in range(len(x)):
+                _id = i
+                yield _id, {
+                    "text": x[i],
+                    "violence": y[i][0],
+                    "directed_vs_generalized": y[i][1],
+                    "gender": y[i][2],
+                    "race": y[i][3],
+                    "national_origin": y[i][4],
+                    "disability": y[i][5],
+                    "religion": y[i][6],
+                    "sexual_orientation": y[i][7],
+                }