Ideiagintza suizidaren identifikazioa sare sozialetan

  1. Sara Gracia 1
  2. Maite Oronoz Antxordoki 2
  3. Alicia Pérez Ramírez 2
  1. 1 Universidad del País Vasco/Euskal Herriko Unibertsitatea
    info
    Universidad del País Vasco/Euskal Herriko Unibertsitatea

    Lejona, España

    ROR https://ror.org/000xsnr85

    Geographic location of the organization Universidad del País Vasco/Euskal Herriko Unibertsitatea
  2. 2 HiTZ: Basque Center for Language Technology
Book:
Ingeniaritza eta arkitektura: V. Ikergazte Nazioarteko Ikerteta Euskaraz. 2023eko maitzaren 17, 18 eta 19 Donostia, Euskal Herria.
  1. Olatz Arbelaitz Gallego
  2. Ainhoa Latatu Nuñez
  3. Elixabete Perez Gaztelu

Publisher: Udako Euskal Unibertsitatea, UEU = Universidad Vasca de Verano

ISBN: 978-84-8438-865-4

Year of publication: 2023

Pages: 123-130

Congress: Ikergazte. Nazioarteko Ikerketa Euskaraz (5. 2023. Donostia)

Type: Conference paper

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Abstract

Suicide has become one of society’s main concerns in recent years. In addition, social media has become part of our everyday life and is often used to express emotions. In this work, a binary classification has been carried out to determine whether or not the content of a message on the Reddit social network is related to suicide. On the one hand, with regard to supervised systems in the state of the art, the best performance has been achieved with the ELECTRA transformer, with an accuracy-rate of 97.9%. On the other hand, it has been concluded that the representations produced by the LDA topic-model can be useful for this task, and to prove this, a baseline classifier has been proposed, which has reached an accuracy of 83.3%.

Data source: Dialnet