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.

  • Rest-Mex 2023 Clustering

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

  • Rest-Mex 2023 Sentiment

    Tourism
    Spanish (Mexico)
    Published in 2023
    359,565
    Tripadvisor opinions
    sentiment analysis

  • HOMO-MEX 2023

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

  • DA-VINCIS 2023

    Social
    Spanish (Mexico)
    Published in 2023
    4,731
    Tweets
    processing events

  • RestMEX-recommendation system

    Tourism
    Spanish (Mexico)
    Published in 2022
    2,263
    TripAdvisor comments
    recommendation systems

  • RestMEX-SA

    Tourism
    Spanish (Mexico)
    Published in 2021
    7,413
    TripAdvisor comments
    sentiment analysis

  • Mexican Aggressiveness Corpus

    Spanish (Mexico)
    Published in 2020
    10,475
    Tweets
    hate detection

  • Spanish Fake News Corpus

    Diverse
    Spanish (Mexico)
    Published in 2020
    971
    News
    fake news detection

  • InterTASS 2020

    Spanish , Spanish (Chile) , Spanish (Costa Rica) , Spanish (Mexico) , Spanish (Peru) , Spanish (Uruguay)
    Published in 2020
    Tweets
    sentiment analysis

  • EmoEVENT

    Spanish , Spanish (Chile) , Spanish (Costa Rica) , Spanish (Mexico) , Spanish (Peru) , Spanish (Uruguay)
    Published in 2020
    8,409
    Tweets
    sentiment analysis

  • IDAT-SP-MEX

    Spanish (Mexico)
    Published in 2019
    3,000
    Tweets
    processing humor

  • MEX-A3T-profiling

    Spanish (Mexico)
    Published in 2018
    5,000
    Tweets
    stylistic analysis, 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.