Datasets

Below is information about Spanish textual data sets created with the goal of solving NLP tasks. In this case, these are collections of texts, generally enriched with annotations.

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Year

  • JOKER 2023 ES

    Social
    Spanish , English
    Published in 2023
    4,235
    Tweets
    hate detection

  • EXIST-2023-ES

    Social
    Spanish , English
    Published in 2023
    4,653
    Tweets
    hate detection

  • CT–CWT–23-ES

    News
    Spanish
    Published in 2023
    29,984
    Tweets
    fake news detection

  • Rest-Mex 2023 Clustering

    News
    Spanish , Spanish (Mexico)
    Published in 2023
    114,550
    News
    topic modeling

  • HOPE-ES 2023

    Social
    Spanish
    Published in 2023
    2,062
    Tweets
    hate detection

  • HOMO-MEX 2023

    Social
    Spanish (Mexico)
    Published in 2023
    11,000
    Tweets
    hate detection

  • DETESTS

    News
    Spanish
    Published in 2022
    5,629
    News comments
    hate detection

  • EXIST-2022-ES

    Spanish
    Published in 2022
    6,226
    Tweets
    hate detection

  • CT–CWT–22-ES

    Spanish
    Published in 2022
    14,990
    Tweets
    fake news detection

  • NewsCom-TOX

    Spanish
    Published in 2021
    4,359
    News comments
    hate detection

  • EXIST-2021-ES

    Spanish
    Published in 2021
    5,701
    Social networks
    hate detection

  • FakeDeS

    COVID, others
    Spanish
    Published in 2021
    1,633
    News
    fake news detection

  • PAN-AP-2021-ES

    Social
    Spanish
    Published in 2021
    300
    Tweets
    hate detection

  • MeOffendES

    Spanish
    Published in 2021
    30,416
    Tweets Instagram comments Youtube comments
    hate detection

  • CheckThat-ES

    Politics
    Spanish
    Published in 2021
    4,990
    Tweets
    fake news detection

If you have published a result better than those on the list, send a message to odesia-comunicacion@lsi.uned.es indicating the result and the DOI of the article, along with a copy of it if it is not published openly.