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.

  • 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

  • DIPROMATS-ES 2023

    Politics
    Spanish , English
    Published in 2023
    9,591
    Tweets
    text classification

  • 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

  • ClinAIS 2023

    Health
    Spanish
    Published in 2023
    1,038
    Clinical notes
    text classification

  • SMM4H-tweets-es-2022

    Health
    Spanish
    Published in 2022
    20,481
    Tweets
    text classification

  • RestMEX-covid-sempahore

    Health
    Spanish (Mexico)
    Published in 2022
    131,471
    News
    text classification

  • ParMEX-2022

    Gastronomy
    Spanish (Mexico)
    Published in 2022
    10,298
    Gastronomy documents
    paraphrasing

  • DETESTS

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

  • EXIST-2022-ES

    Spanish
    Published in 2022
    6,226
    Tweets
    hate detection

  • ADoBo

    Spanish
    Published in 2021
    Laws
    text classification

  • 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

  • PAN-AP-2021-ES

    Social
    Spanish
    Published in 2021
    300
    Tweets
    hate 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.