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Dataset Card for "guardian_authorship"

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

Supported Tasks and Leaderboards

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Languages

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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

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

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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

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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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, @eltoto1219, @malikaltakrori for adding this dataset.

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