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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/81923

    Título
    Automated image extraction from Instagram for social research
    Autor
    Varela-Rodríguez, Miguel
    Vicente-Mariño, Miguel
    Año del Documento
    2020
    Editorial
    Association for Computing Machinery
    Documento Fuente
    TEEM'20: Eighth International Conference on Technological Ecosystems for Enhancing MulticulturalityOctober 21 - 23, 2020
    Résumé
    The use of social media data in social research has grown exponentially since the early 2010s, with many social researchers incorporating some degree of social media analysis. Following the 2018 Cambridge Analytica controversy, most social media providers locked access to their users’ data, leaving researchers with limited options to study the information in it. Scholars have taken different stands, advocating data policies that allow for critical research, achieving partnerships with data providers, or—sometimes—violating the Terms of Use of the platforms to access the information. Despite the limitations, great progress has been made using text-based data, while image-based methodologies remain limited, partly because of the lockout. This paper proposes a methodology for automated image extraction from Instagram, using Instalooter. It presents the necessary setup and steps to obtain images based on a series of search parameters before discussing the ethical implications of its potential use.
    Revisión por pares
    SI
    DOI
    10.1145/3434780.3436650
    Version del Editor
    https://dl.acm.org/doi/10.1145/3434780.3436650
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/81923
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
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    • DEP68 - Artículos de revista [202]
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    TEEM 20 Scraping Images.pdf
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