1 dataset found

  1. PAN15 Author Profiling

    • zenodo.org
    Updated Apr 9, 2020
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    Francisco Rangel; Fabio Celli; Paolo Rosso; Martin Potthast; Martin Potthast; Benno Stein; Benno Stein; Walter Daelemans; Francisco Rangel; Fabio Celli; Paolo Rosso; Walter Daelemans (2020). PAN15 Author Profiling [Dataset]. http://doi.org/10.5281/zenodo.3745945
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    Unique identifier
    https://doi.org/10.5281/zenodo.3745945
    Dataset updated
    Apr 9, 2020
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Francisco Rangel; Fabio Celli; Paolo Rosso; Martin Potthast; Martin Potthast; Benno Stein; Benno Stein; Walter Daelemans; Francisco Rangel; Fabio Celli; Paolo Rosso; Walter Daelemans
    Description

    We provide a data set that consists of Twitter tweets in English, Spanish, Italian and Dutch. With regard to age, we will consider the following classes: 18-24, 25-34, 35-49, 50-xx. With regard to personality traits, for each trait we will provide scores (between -0.5 and 0.5).

    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; Fabio Celli; Paolo Rosso; Martin Potthast; Martin Potthast; Benno Stein; Benno Stein; Walter Daelemans; Francisco Rangel; Fabio Celli; Paolo Rosso; Walter Daelemans (2020). PAN15 Author Profiling [Dataset]. http://doi.org/10.5281/zenodo.3745945
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PAN15 Author Profiling

Explore at:
11 scholarly articles cite this dataset (View in Google Scholar)
Unique identifier
https://doi.org/10.5281/zenodo.3745945
Dataset updated
Apr 9, 2020
Dataset provided by
Zenodohttp://zenodo.org/
Authors
Francisco Rangel; Fabio Celli; Paolo Rosso; Martin Potthast; Martin Potthast; Benno Stein; Benno Stein; Walter Daelemans; Francisco Rangel; Fabio Celli; Paolo Rosso; Walter Daelemans
Description

We provide a data set that consists of Twitter tweets in English, Spanish, Italian and Dutch. With regard to age, we will consider the following classes: 18-24, 25-34, 35-49, 50-xx. With regard to personality traits, for each trait we will provide scores (between -0.5 and 0.5).

More information about the task: Link

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