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2 datasets found
  1. Z

    Data from: PAN20 Authorship Analysis: Authorship Verification

    • data.niaid.nih.gov
    • zenodo.org
    Updated Nov 20, 2023
  2. Z

    PAN20 Authorship Analysis: Style Change Detection

    • data.niaid.nih.gov
    Updated Aug 10, 2021
    + more versions
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Stein, Benno (2023). PAN20 Authorship Analysis: Authorship Verification [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_3716402

Data from: PAN20 Authorship Analysis: Authorship Verification

Related Article
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Dataset updated
Nov 20, 2023
Dataset provided by
Bevendorff, Janek
Kestemont, Mike
Stein, Benno
Potthast, Martin
Stamatatos, Efstathios
Manjavacas, Enrique
Description

Task Authorship verification is the task of deciding whether two texts have been written by the same author based on comparing the texts' writing styles. In the coming three years at PAN 2020 to PAN 2022, we develop a new experimental setup that addresses three key questions in authorship verification that have not been studied at scale to date: Year 1 (PAN 2020): Closed-set verficiation.Given a large training dataset comprising of known authors who have written about a given set of topics, the test dataset contains verification cases from a subset of the authors and topics found in the training data. Year 2 (PAN 2021): Open-set verification.Given the training dataset of Year 1, the test dataset contains verification cases from previously unseen authors and topics. Year 3 (PAN 2022): Suprise task.The task of the last year of this evaluation cycle (to be announced at a later time) will be designed with an eye on realism and practical application. This evaluation cycle on authorship verification provides for a renewed challenge of increasing difficulty within a large-scale evaluation. We invite you to plan ahead and participate in all three of these tasks. More information at: PAN @ CLEF 2020 - Authorship Verification

Citing the Dataset If you use this dataset for your research, please be sure to cite the following paper:Sebastian Bischoff, Niklas Deckers, Marcel Schliebs, Ben Thies, Matthias Hagen, Efstathios Stamatatos, Benno Stein, and Martin Potthast. The Importance of Suppressing Domain Style in Authorship Analysis. CoRR, abs/2005.14714, May 2020. Bibtex: @Article{stein:2020k, author = {Sebastian Bischoff and Niklas Deckers and Marcel Schliebs and Ben Thies and Matthias Hagen and Efstathios Stamatatos and Benno Stein and Martin Potthast}, journal = {CoRR}, month = may, title = {{The Importance of Suppressing Domain Style in Authorship Analysis}}, url = {https://arxiv.org/abs/2005.14714}, volume = {abs/2005.14714}, year = 2020 }

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