• Resumo

    Utilizando Análise de Sentimentos e SVM na Classificação de Tweets Depressivos

    Data de publicação: 29/04/2021

    The number of depression cases has grown worldwide. The World
    Health Organization estimates that 5.8% of the Brazilian population
    already present depression symptoms. In the world, 4.8% of
    the entire population has presented some symptoms. These data
    are alarming because they represent about 12 million people only
    in Brazil and 368 million worldwide. Therefore, it is essential to
    build applications that adequately identify the population’s feelings
    about depression to drive public health policies. Appropriate policies
    can save money on public health and keep people active. Thus,
    this work investigates how to apply machine learning in classifying
    depression posts on Tweeter. The data were extracted from the
    social media network, reaching a total of 31.177 tweets classified as
    depressive and non-depressive. The application was implemented
    in Python with Pandas and SciKit Learning. Results have shown
    that SVM overcomes the Naive Bayes algorithm and can reach an
    accuracy of 94%, precision of 91%, a recall of 91%, and an F1 Score
    of 91%.

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O Computer on the Beach é um evento técnico-científico que visa reunir profissionais, pesquisadores e acadêmicos da área de Computação, a fim de discutir as tendências de pesquisa e mercado da computação em suas mais diversas áreas.

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