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Efstathios/guardian_authorship

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

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Table of Contents

Dataset Description

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. crosstopic1 => row 1:P S U&W ). 2- The cross-genre scenarios are based on Table-5 in the same paper. (Ex. crossgenre1 => 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 sametopic and split the data 60-40 use: trainds = loaddataset('guardianauthorship', name="crosstopic<<#>>", split='train[:60%]+validation[:60%]+test[:60%]') testsds = loaddataset('guardianauthorship', name="crosstopic_<<#>>", 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

Languages

More Information Needed

Dataset Structure

Data Instances

crossgenre1
  • —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
}
crossgenre2
  • —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
}
crossgenre3
  • —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
}
crossgenre4
  • —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
}
crosstopic1
  • —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.

crossgenre1
  • —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.
crossgenre2
  • —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.
crossgenre3
  • —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.
crossgenre4
  • —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.
crosstopic1
  • —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

nametrainvalidationtest
crossgenre163112269
crossgenre26362319
crossgenre36390291
crossgenre463117264
crosstopic111262207

Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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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.