
# Dataset Card for "guardian_authorship"

## 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:** [http://www.icsd.aegean.gr/lecturers/stamatatos/papers/JLP2013.pdf](http://www.icsd.aegean.gr/lecturers/stamatatos/papers/JLP2013.pdf)
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 49.61 MB
- **Size of the generated dataset:** 38.98 MB
- **Total amount of disk used:** 88.59 MB

### Dataset Summary

A dataset cross-topic authorship attribution. The dataset is provided by Stamatatos 2013.
1- The cross-topic scenarios are based on Table-4 in Stamatatos 2017 (Ex. cross_topic_1 => row 1:P S U&W ).
2- The cross-genre scenarios are based on Table-5 in the same paper. (Ex. cross_genre_1 => row 1:B P S&U&W).

3- The same-topic/genre scenario is created by grouping all the datasts as follows.
For ex., to use same_topic and split the data 60-40 use:
train_ds = load_dataset('guardian_authorship', name="cross_topic_<<#>>",
                        split='train[:60%]+validation[:60%]+test[:60%]')
tests_ds = load_dataset('guardian_authorship', name="cross_topic_<<#>>",
                        split='train[-40%:]+validation[-40%:]+test[-40%:]')

IMPORTANT: train+validation+test[:60%] will generate the wrong splits because the data is imbalanced

* See https://huggingface.co/docs/datasets/splits.html for detailed/more examples

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Dataset Structure

### Data Instances

#### cross_genre_1

- **Size of downloaded dataset files:** 3.10 MB
- **Size of the generated dataset:** 2.74 MB
- **Total amount of disk used:** 5.84 MB

An example of 'train' looks as follows.
```
{
    "article": "File 1a\n",
    "author": 0,
    "topic": 4
}
```

#### cross_genre_2

- **Size of downloaded dataset files:** 3.10 MB
- **Size of the generated dataset:** 2.74 MB
- **Total amount of disk used:** 5.84 MB

An example of 'validation' looks as follows.
```
{
    "article": "File 1a\n",
    "author": 0,
    "topic": 1
}
```

#### cross_genre_3

- **Size of downloaded dataset files:** 3.10 MB
- **Size of the generated dataset:** 2.74 MB
- **Total amount of disk used:** 5.84 MB

An example of 'validation' looks as follows.
```
{
    "article": "File 1a\n",
    "author": 0,
    "topic": 2
}
```

#### cross_genre_4

- **Size of downloaded dataset files:** 3.10 MB
- **Size of the generated dataset:** 2.74 MB
- **Total amount of disk used:** 5.84 MB

An example of 'validation' looks as follows.
```
{
    "article": "File 1a\n",
    "author": 0,
    "topic": 3
}
```

#### cross_topic_1

- **Size of downloaded dataset files:** 3.10 MB
- **Size of the generated dataset:** 2.34 MB
- **Total amount of disk used:** 5.43 MB

An example of 'validation' looks as follows.
```
{
    "article": "File 1a\n",
    "author": 0,
    "topic": 1
}
```

### Data Fields

The data fields are the same among all splits.

#### cross_genre_1
- `author`: a classification label, with possible values including `catherinebennett` (0), `georgemonbiot` (1), `hugoyoung` (2), `jonathanfreedland` (3), `martinkettle` (4).
- `topic`: a classification label, with possible values including `Politics` (0), `Society` (1), `UK` (2), `World` (3), `Books` (4).
- `article`: a `string` feature.

#### cross_genre_2
- `author`: a classification label, with possible values including `catherinebennett` (0), `georgemonbiot` (1), `hugoyoung` (2), `jonathanfreedland` (3), `martinkettle` (4).
- `topic`: a classification label, with possible values including `Politics` (0), `Society` (1), `UK` (2), `World` (3), `Books` (4).
- `article`: a `string` feature.

#### cross_genre_3
- `author`: a classification label, with possible values including `catherinebennett` (0), `georgemonbiot` (1), `hugoyoung` (2), `jonathanfreedland` (3), `martinkettle` (4).
- `topic`: a classification label, with possible values including `Politics` (0), `Society` (1), `UK` (2), `World` (3), `Books` (4).
- `article`: a `string` feature.

#### cross_genre_4
- `author`: a classification label, with possible values including `catherinebennett` (0), `georgemonbiot` (1), `hugoyoung` (2), `jonathanfreedland` (3), `martinkettle` (4).
- `topic`: a classification label, with possible values including `Politics` (0), `Society` (1), `UK` (2), `World` (3), `Books` (4).
- `article`: a `string` feature.

#### cross_topic_1
- `author`: a classification label, with possible values including `catherinebennett` (0), `georgemonbiot` (1), `hugoyoung` (2), `jonathanfreedland` (3), `martinkettle` (4).
- `topic`: a classification label, with possible values including `Politics` (0), `Society` (1), `UK` (2), `World` (3), `Books` (4).
- `article`: a `string` feature.

### Data Splits

|    name     |train|validation|test|
|-------------|----:|---------:|---:|
|cross_genre_1|   63|       112| 269|
|cross_genre_2|   63|        62| 319|
|cross_genre_3|   63|        90| 291|
|cross_genre_4|   63|       117| 264|
|cross_topic_1|  112|        62| 207|

## Dataset Creation

### Curation Rationale

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Citation Information

```
@article{article,
    author = {Stamatatos, Efstathios},
    year = {2013},
    month = {01},
    pages = {421-439},
    title = {On the robustness of authorship attribution based on character n-gram features},
    volume = {21},
    journal = {Journal of Law and Policy}
}

@inproceedings{stamatatos2017authorship,
    title={Authorship attribution using text distortion},
    author={Stamatatos, Efstathios},
    booktitle={Proc. of the 15th Conf. of the European Chapter of the Association for Computational Linguistics},
    volume={1}
    pages={1138--1149},
    year={2017}
}

```


### Contributions

Thanks to [@thomwolf](https://github.com/thomwolf), [@eltoto1219](https://github.com/eltoto1219), [@malikaltakrori](https://github.com/malikaltakrori) for adding this dataset.
task_categories:text-classification task_ids:multi-class-classification task_ids:topic-classification annotations_creators:found language_creators:found multilinguality:monolingual size_categories:1K<n<10K source_datasets:original language:en license:unknown region:us
{"annotations_creators": ["found"], "language_creators": ["found"], "language": ["en"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["multi-class-classification", "topic-classification"], "pretty_name": "GuardianAuthorship", "dataset_info": [{"config_name": "cross_topic_1", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 677054, "num_examples": 112}, {"name": "test", "num_bytes": 1283126, "num_examples": 207}, {"name": "validation", "num_bytes": 374390, "num_examples": 62}], "download_size": 3100749, "dataset_size": 2334570}, {"config_name": "cross_genre_1", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 406144, "num_examples": 63}, {"name": "test", "num_bytes": 1657512, "num_examples": 269}, {"name": "validation", "num_bytes": 677054, "num_examples": 112}], "download_size": 3100749, "dataset_size": 2740710}, {"config_name": "cross_topic_2", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 677054, "num_examples": 112}, {"name": "test", "num_bytes": 1104764, "num_examples": 179}, {"name": "validation", "num_bytes": 552752, "num_examples": 90}], "download_size": 3100749, "dataset_size": 2334570}, {"config_name": "cross_topic_3", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 677054, "num_examples": 112}, {"name": "test", "num_bytes": 927138, "num_examples": 152}, {"name": "validation", "num_bytes": 730378, "num_examples": 117}], "download_size": 3100749, "dataset_size": 2334570}, {"config_name": "cross_topic_4", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 374390, "num_examples": 62}, {"name": "test", "num_bytes": 1283126, "num_examples": 207}, {"name": "validation", "num_bytes": 677054, "num_examples": 112}], "download_size": 3100749, "dataset_size": 2334570}, {"config_name": "cross_topic_5", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 374390, "num_examples": 62}, {"name": "test", "num_bytes": 1407428, "num_examples": 229}, {"name": "validation", "num_bytes": 552752, "num_examples": 90}], "download_size": 3100749, "dataset_size": 2334570}, {"config_name": "cross_topic_6", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 374390, "num_examples": 62}, {"name": "test", "num_bytes": 1229802, "num_examples": 202}, {"name": "validation", "num_bytes": 730378, "num_examples": 117}], "download_size": 3100749, "dataset_size": 2334570}, {"config_name": "cross_topic_7", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 552752, "num_examples": 90}, {"name": "test", "num_bytes": 1104764, "num_examples": 179}, {"name": "validation", "num_bytes": 677054, "num_examples": 112}], "download_size": 3100749, "dataset_size": 2334570}, {"config_name": "cross_topic_8", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 552752, "num_examples": 90}, {"name": "test", "num_bytes": 1407428, "num_examples": 229}, {"name": "validation", "num_bytes": 374390, "num_examples": 62}], "download_size": 3100749, "dataset_size": 2334570}, {"config_name": "cross_topic_9", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 552752, "num_examples": 90}, {"name": "test", "num_bytes": 1051440, "num_examples": 174}, {"name": "validation", "num_bytes": 730378, "num_examples": 117}], "download_size": 3100749, "dataset_size": 2334570}, {"config_name": "cross_topic_10", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 730378, "num_examples": 117}, {"name": "test", "num_bytes": 927138, "num_examples": 152}, {"name": "validation", "num_bytes": 677054, "num_examples": 112}], "download_size": 3100749, "dataset_size": 2334570}, {"config_name": "cross_topic_11", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 730378, "num_examples": 117}, {"name": "test", "num_bytes": 1229802, "num_examples": 202}, {"name": "validation", "num_bytes": 374390, "num_examples": 62}], "download_size": 3100749, "dataset_size": 2334570}, {"config_name": "cross_topic_12", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 730378, "num_examples": 117}, {"name": "test", "num_bytes": 1051440, "num_examples": 174}, {"name": "validation", "num_bytes": 552752, "num_examples": 90}], "download_size": 3100749, "dataset_size": 2334570}, {"config_name": "cross_genre_2", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 406144, "num_examples": 63}, {"name": "test", "num_bytes": 1960176, "num_examples": 319}, {"name": "validation", "num_bytes": 374390, "num_examples": 62}], "download_size": 3100749, "dataset_size": 2740710}, {"config_name": "cross_genre_3", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 406144, "num_examples": 63}, {"name": "test", "num_bytes": 1781814, "num_examples": 291}, {"name": "validation", "num_bytes": 552752, "num_examples": 90}], "download_size": 3100749, "dataset_size": 2740710}, {"config_name": "cross_genre_4", "features": [{"name": "author", "dtype": {"class_label": {"names": {"0": "catherinebennett", "1": "georgemonbiot", "2": "hugoyoung", "3": "jonathanfreedland", "4": "martinkettle", "5": "maryriddell", "6": "nickcohen", "7": "peterpreston", "8": "pollytoynbee", "9": "royhattersley", "10": "simonhoggart", "11": "willhutton", "12": "zoewilliams"}}}}, {"name": "topic", "dtype": {"class_label": {"names": {"0": "Politics", "1": "Society", "2": "UK", "3": "World", "4": "Books"}}}}, {"name": "article", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 406144, "num_examples": 63}, {"name": "test", "num_bytes": 1604188, "num_examples": 264}, {"name": "validation", "num_bytes": 730378, "num_examples": 117}], "download_size": 3100749, "dataset_size": 2740710}]}
TAGS
#task_categories-text-classification #task_ids-multi-class-classification #task_ids-topic-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-English #license-unknown #region-us 

Dataset Card for "guardian\_authorship"
=======================================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ Personal and Sensitive Information
* Considerations for Using the Data
	+ Social Impact of Dataset
	+ Discussion of Biases
	+ Other Known Limitations
* Additional Information
	+ Dataset Curators
	+ Licensing Information
	+ Citation Information
	+ Contributions


Dataset Description
-------------------


* Homepage: URL
* Repository:
* Paper:
* Point of Contact:
* Size of downloaded dataset files: 49.61 MB
* Size of the generated dataset: 38.98 MB
* Total amount of disk used: 88.59 MB


### Dataset Summary


A dataset cross-topic authorship attribution. The dataset is provided by Stamatatos 2013.
1- The cross-topic scenarios are based on Table-4 in Stamatatos 2017 (Ex. cross\_topic\_1 => row 1:P S U&W ).
2- The cross-genre scenarios are based on Table-5 in the same paper. (Ex. cross\_genre\_1 => row 1:B P S&U&W).


3- The same-topic/genre scenario is created by grouping all the datasts as follows.
For ex., to use same\_topic and split the data 60-40 use:
train\_ds = load\_dataset('guardian\_authorship', name="cross\_topic\_<<#>>",
split='train[:60%]+validation[:60%]+test[:60%]')
tests\_ds = load\_dataset('guardian\_authorship', name="cross\_topic\_<<#>>",
split='train[-40%:]+validation[-40%:]+test[-40%:]')


IMPORTANT: train+validation+test[:60%] will generate the wrong splits because the data is imbalanced


* See URL for detailed/more examples


### Supported Tasks and Leaderboards


### Languages


Dataset Structure
-----------------


### Data Instances


#### cross\_genre\_1


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'train' looks as follows.


#### cross\_genre\_2


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'validation' looks as follows.


#### cross\_genre\_3


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'validation' looks as follows.


#### cross\_genre\_4


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'validation' looks as follows.


#### cross\_topic\_1


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.34 MB
* Total amount of disk used: 5.43 MB


An example of 'validation' looks as follows.


### Data Fields


The data fields are the same among all splits.


#### cross\_genre\_1


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature.


#### cross\_genre\_2


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature.


#### cross\_genre\_3


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature.


#### cross\_genre\_4


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature.


#### cross\_topic\_1


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature.


### Data Splits



Dataset Creation
----------------


### Curation Rationale


### Source Data


#### Initial Data Collection and Normalization


#### Who are the source language producers?


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


Additional Information
----------------------


### Dataset Curators


### Licensing Information


### Contributions


Thanks to @thomwolf, @eltoto1219, @malikaltakrori for adding this dataset.



### Dataset Summary


A dataset cross-topic authorship attribution. The dataset is provided by Stamatatos 2013.
1- The cross-topic scenarios are based on Table-4 in Stamatatos 2017 (Ex. cross\_topic\_1 => row 1:P S U&W ).
2- The cross-genre scenarios are based on Table-5 in the same paper. (Ex. cross\_genre\_1 => row 1:B P S&U&W).


3- The same-topic/genre scenario is created by grouping all the datasts as follows.
For ex., to use same\_topic and split the data 60-40 use:
train\_ds = load\_dataset('guardian\_authorship', name="cross\_topic\_<<#>>",
split='train[:60%]+validation[:60%]+test[:60%]')
tests\_ds = load\_dataset('guardian\_authorship', name="cross\_topic\_<<#>>",
split='train[-40%:]+validation[-40%:]+test[-40%:]')


IMPORTANT: train+validation+test[:60%] will generate the wrong splits because the data is imbalanced


* See URL for detailed/more examples ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### cross\_genre\_1


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'train' looks as follows. #### cross\_genre\_2


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'validation' looks as follows. #### cross\_genre\_3


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'validation' looks as follows. #### cross\_genre\_4


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'validation' looks as follows. #### cross\_topic\_1


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.34 MB
* Total amount of disk used: 5.43 MB


An example of 'validation' looks as follows. ### Data Fields


The data fields are the same among all splits. #### cross\_genre\_1


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature. #### cross\_genre\_2


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature. #### cross\_genre\_3


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature. #### cross\_genre\_4


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature. #### cross\_topic\_1


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature. ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information ### Contributions


Thanks to @thomwolf, @eltoto1219, @malikaltakrori for adding this dataset.
TAGS
#task_categories-text-classification #task_ids-multi-class-classification #task_ids-topic-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-English #license-unknown #region-us 
 ### Dataset Summary


A dataset cross-topic authorship attribution. The dataset is provided by Stamatatos 2013.
1- The cross-topic scenarios are based on Table-4 in Stamatatos 2017 (Ex. cross\_topic\_1 => row 1:P S U&W ).
2- The cross-genre scenarios are based on Table-5 in the same paper. (Ex. cross\_genre\_1 => row 1:B P S&U&W).


3- The same-topic/genre scenario is created by grouping all the datasts as follows.
For ex., to use same\_topic and split the data 60-40 use:
train\_ds = load\_dataset('guardian\_authorship', name="cross\_topic\_<<#>>",
split='train[:60%]+validation[:60%]+test[:60%]')
tests\_ds = load\_dataset('guardian\_authorship', name="cross\_topic\_<<#>>",
split='train[-40%:]+validation[-40%:]+test[-40%:]')


IMPORTANT: train+validation+test[:60%] will generate the wrong splits because the data is imbalanced


* See URL for detailed/more examples ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### cross\_genre\_1


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'train' looks as follows. #### cross\_genre\_2


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'validation' looks as follows. #### cross\_genre\_3


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'validation' looks as follows. #### cross\_genre\_4


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'validation' looks as follows. #### cross\_topic\_1


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.34 MB
* Total amount of disk used: 5.43 MB


An example of 'validation' looks as follows. ### Data Fields


The data fields are the same among all splits. #### cross\_genre\_1


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature. #### cross\_genre\_2


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature. #### cross\_genre\_3


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature. #### cross\_genre\_4


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature. #### cross\_topic\_1


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature. ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information ### Contributions


Thanks to @thomwolf, @eltoto1219, @malikaltakrori for adding this dataset.
passage: TAGS
#task_categories-text-classification #task_ids-multi-class-classification #task_ids-topic-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-English #license-unknown #region-us 
### Dataset Summary


A dataset cross-topic authorship attribution. The dataset is provided by Stamatatos 2013.
1- The cross-topic scenarios are based on Table-4 in Stamatatos 2017 (Ex. cross\_topic\_1 => row 1:P S U&W ).
2- The cross-genre scenarios are based on Table-5 in the same paper. (Ex. cross\_genre\_1 => row 1:B P S&U&W).


3- The same-topic/genre scenario is created by grouping all the datasts as follows.
For ex., to use same\_topic and split the data 60-40 use:
train\_ds = load\_dataset('guardian\_authorship', name="cross\_topic\_<<#>>",
split='train[:60%]+validation[:60%]+test[:60%]')
tests\_ds = load\_dataset('guardian\_authorship', name="cross\_topic\_<<#>>",
split='train[-40%:]+validation[-40%:]+test[-40%:]')


IMPORTANT: train+validation+test[:60%] will generate the wrong splits because the data is imbalanced


* See URL for detailed/more examples### Supported Tasks and Leaderboards### Languages


Dataset Structure
-----------------### Data Instances#### cross\_genre\_1


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'train' looks as follows. passage: #### cross\_genre\_2


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'validation' looks as follows.#### cross\_genre\_3


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'validation' looks as follows.#### cross\_genre\_4


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.74 MB
* Total amount of disk used: 5.84 MB


An example of 'validation' looks as follows.#### cross\_topic\_1


* Size of downloaded dataset files: 3.10 MB
* Size of the generated dataset: 2.34 MB
* Total amount of disk used: 5.43 MB


An example of 'validation' looks as follows.### Data Fields


The data fields are the same among all splits.#### cross\_genre\_1


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature.#### cross\_genre\_2


* 'author': a classification label, with possible values including 'catherinebennett' (0), 'georgemonbiot' (1), 'hugoyoung' (2), 'jonathanfreedland' (3), 'martinkettle' (4).
* 'topic': a classification label, with possible values including 'Politics' (0), 'Society' (1), 'UK' (2), 'World' (3), 'Books' (4).
* 'article': a 'string' feature.