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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/75138

    Título
    Machine Learning algorithms to address the polarity and stigma of mental health disclosures on Instagram
    Autor
    Merayo Álvarez, NoemíAutoridad UVA Orcid
    Ayuso Lanchares, AlbaAutoridad UVA Orcid
    González Sanguino, Teresa ClaraAutoridad UVA Orcid
    Año del Documento
    2025
    Editorial
    Wiley
    Descripción
    Producción Científica
    Documento Fuente
    Expert Systems, 2025, vol. 42, n. 2, e13832
    Résumé
    This research explores the social response to disclosures and conversations about mental health on social media, which is a pioneering and innovative approach. Unlike previous studies, which focused predominantly on psychopathological aspects, this study explores how communities react to conversations about mental health on Instagram, one of the favourite social media platforms among young people, breaking new ground not only in the Spanish context, but also on a global scale, filling a gap in international research. The study created a novel corpus by collecting and labelling comments on Instagram posts related to celebrity mental health disclosures, categorising them by polarity (positive, negative, neutral) and stigma. Additionally, the research implements machine learning algorithms to detect stigma and polarity in mental health disclosures on Instagram. While traditional techniques like Support Vector Machine (SVM) and RF (Random Forest) displayed decent performance with lower computational loads, advanced deep learning and BERT (Bidirectional Encoder Representation from Transformers) algorithms achieved outstanding results. In fact, BERT models achieve around 96% accuracy in polarity and stigma detection, while deep learning models achieve 80% for polarity and 87% for stigma, very high accuracy metrics. This research contributes significantly to understanding the impact of mental health discussions on social media, offering insights that can reduce stigma and raise awareness. Artificial intelligence can be used for more responsible use of social media and effective management of mental health problems in digital environments.
    Materias Unesco
    1203 Ciencia de Los Ordenadores
    61 Psicología
    5910.02 Medios de Comunicación de Masas
    Palabras Clave
    Instagram
    machine learning
    mental health
    natural language processing
    sentiment analysis
    social networks
    stigma
    ISSN
    0266-4720
    Revisión por pares
    SI
    DOI
    10.1111/exsy.13832
    Patrocinador
    Universidad de Valladolid
    Version del Editor
    https://onlinelibrary.wiley.com/doi/full/10.1111/exsy.13832
    Propietario de los Derechos
    © 2025 The Author(s)
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/75138
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
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