@inproceedings{marmol-romero-etal-2024-mentalriskes,
    title = "{M}ental{R}isk{ES}: A New Corpus for Early Detection of Mental Disorders in {S}panish",
    author = "M{\'a}rmol Romero, Alba M.  and
      Moreno Mu{\~n}oz, Adri{\'a}n  and
      Plaza-del-Arco, Flor Miriam  and
      Molina Gonz{\'a}lez, M. Dolores  and
      Mart{\'\i}n Valdivia, Mar{\'\i}a Teresa  and
      Ure{\~n}a-L{\'o}pez, L. Alfonso  and
      Montejo R{\'a}ez, Arturo",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.978",
    pages = "11204--11214",
    abstract = "With mental health issues on the rise on the Web, especially among young people, there is a growing need for effective identification and intervention. In this paper, we introduce a new open-sourced corpus for the early detection of mental disorders in Spanish, focusing on eating disorders, depression, and anxiety. It consists of user messages posted on groups within the Telegram message platform and contains over 1,300 subjects with more than 45,000 messages posted in different public Telegram groups. This corpus has been manually annotated via crowdsourcing and is prepared for its use in several Natural Language Processing tasks including text classification and regression tasks. The samples in the corpus include both text and time data. To provide a benchmark for future research, we conduct experiments on text classification and regression by using state-of-the-art transformer-based models.",
}

With mental health issues on the rise on the Web, especially among young people, there is a growing need for effective identification and intervention. In this paper, we introduce a new open-sourced corpus for the early detection of mental disorders in Spanish, focusing on eating disorders, depression, and anxiety. It consists of user messages posted on groups within the Telegram message platform and contains over 1,300 subjects with more than 45,000 messages posted in different public Telegram groups. This corpus has been manually annotated via crowdsourcing and is prepared for its use in several Natural Language Processing tasks including text classification and regression tasks. The samples in the corpus include both text and time data. To provide a benchmark for future research, we conduct experiments on text classification and regression by using state-of-the-art transformer-based models.
M{\'a}rmol Romero, Alba M. Moreno Mu{\~n}oz, Adri{\'a}n Plaza-del-Arco, Flor Miriam Molina Gonz{\'a}lez, M. Dolores Mart{\'\i}n Valdivia, Mar{\'\i}a Teresa Ure{\~n}a-L{\'o}pez, L. Alfonso Montejo R{\'a}ez, Arturo
MentalRiskES: A New Corpus for Early Detection of Mental Disorders in Spanish