1 dataset found
  1. PAN16 Author Profiling

    • zenodo.org
    Updated Apr 9, 2020
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    Francisco Rangel; Paolo Rosso; Ben Verhoeven; Walter Daelemans; Martin Potthast; Martin Potthast; Benno Stein; Benno Stein; Francisco Rangel; Paolo Rosso; Ben Verhoeven; Walter Daelemans (2020). PAN16 Author Profiling [Dataset]. http://doi.org/10.5281/zenodo.3745963
    Explore at:
    Dataset updated
    Apr 9, 2020
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Francisco Rangel; Paolo Rosso; Ben Verhoeven; Walter Daelemans; Martin Potthast; Martin Potthast; Benno Stein; Benno Stein; Francisco Rangel; Paolo Rosso; Ben Verhoeven; Walter Daelemans
    Description

    We provide a training data set that consists of Twitter tweets in English, Spanish and Dutch.

    The English and Spanish datasets are labeled with age and gender, whereas the Dutch one only with gender. With regard to age, we will consider the following classes: 18-24, 25-34, 35-49, 50-64, 65-xx.

    Remark. Due to Twitter's privacy policy we cannot provide tweets directly, but only URLs referring to them. You will have to download them yourself. For your convenience, we provide a download software for this. We expect participants to extract gender and age information only from the textual part of a tweet and to discard any other meta information that may be provided by Twitter's API. When we evaluate your software at our site, we do not expect it downloads tweets. We will do this beforehand.

    More information about the task: Link

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Francisco Rangel; Paolo Rosso; Ben Verhoeven; Walter Daelemans; Martin Potthast; Martin Potthast; Benno Stein; Benno Stein; Francisco Rangel; Paolo Rosso; Ben Verhoeven; Walter Daelemans (2020). PAN16 Author Profiling [Dataset]. http://doi.org/10.5281/zenodo.3745963
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PAN16 Author Profiling

Explore at:
Dataset updated
Apr 9, 2020
Dataset provided by
Zenodohttp://zenodo.org/
Authors
Francisco Rangel; Paolo Rosso; Ben Verhoeven; Walter Daelemans; Martin Potthast; Martin Potthast; Benno Stein; Benno Stein; Francisco Rangel; Paolo Rosso; Ben Verhoeven; Walter Daelemans
Description

We provide a training data set that consists of Twitter tweets in English, Spanish and Dutch.

The English and Spanish datasets are labeled with age and gender, whereas the Dutch one only with gender. With regard to age, we will consider the following classes: 18-24, 25-34, 35-49, 50-64, 65-xx.

Remark. Due to Twitter's privacy policy we cannot provide tweets directly, but only URLs referring to them. You will have to download them yourself. For your convenience, we provide a download software for this. We expect participants to extract gender and age information only from the textual part of a tweet and to discard any other meta information that may be provided by Twitter's API. When we evaluate your software at our site, we do not expect it downloads tweets. We will do this beforehand.

More information about the task: Link

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