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  • Source: SBSI 2021. Conference titles: XVII Brazilian Symposium on Information Systems. Unidade: EACH

    Subjects: REDES SOCIAIS, ELEIÇÃO PRESIDENCIAL, PROCESSAMENTO DE LINGUAGEM NATURAL

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    • ABNT

      FERREIRA, Gabriel Estavaringo et al. Social bots detection in Brazilian presidential elections using natural language processing. 2021, Anais.. Uberlândia: Federal University of Uberlândia, 2021. Disponível em: https://dl.acm.org/doi/pdf/10.1145/3466933.3466991. Acesso em: 30 abr. 2024.
    • APA

      Ferreira, G. E., Santos, B. L., Ó, M. T. do, Braz, R. R., & Digiampietri, L. A. (2021). Social bots detection in Brazilian presidential elections using natural language processing. In SBSI 2021. Uberlândia: Federal University of Uberlândia. Recuperado de https://dl.acm.org/doi/pdf/10.1145/3466933.3466991
    • NLM

      Ferreira GE, Santos BL, Ó MT do, Braz RR, Digiampietri LA. Social bots detection in Brazilian presidential elections using natural language processing [Internet]. SBSI 2021. 2021 ;[citado 2024 abr. 30 ] Available from: https://dl.acm.org/doi/pdf/10.1145/3466933.3466991
    • Vancouver

      Ferreira GE, Santos BL, Ó MT do, Braz RR, Digiampietri LA. Social bots detection in Brazilian presidential elections using natural language processing [Internet]. SBSI 2021. 2021 ;[citado 2024 abr. 30 ] Available from: https://dl.acm.org/doi/pdf/10.1145/3466933.3466991
  • Source: SBSI 2021. Conference titles: XVII Brazilian Symposium on Information Systems. Unidade: EACH

    Subjects: REDES SOCIAIS, PESQUISADORES

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      FONSECA, Felipe P. C. e DIGIAMPIETRI, Luciano Antonio. Improving researcher’s area of expertise identification using TF-IDF Characters N-grams. 2021, Anais.. Uberlândia: Federal University of Uberlândia, 2021. Disponível em: https://dl.acm.org/doi/pdf/10.1145/3466933.3466984. Acesso em: 30 abr. 2024.
    • APA

      Fonseca, F. P. C., & Digiampietri, L. A. (2021). Improving researcher’s area of expertise identification using TF-IDF Characters N-grams. In SBSI 2021. Uberlândia: Federal University of Uberlândia. Recuperado de https://dl.acm.org/doi/pdf/10.1145/3466933.3466984
    • NLM

      Fonseca FPC, Digiampietri LA. Improving researcher’s area of expertise identification using TF-IDF Characters N-grams [Internet]. SBSI 2021. 2021 ;[citado 2024 abr. 30 ] Available from: https://dl.acm.org/doi/pdf/10.1145/3466933.3466984
    • Vancouver

      Fonseca FPC, Digiampietri LA. Improving researcher’s area of expertise identification using TF-IDF Characters N-grams [Internet]. SBSI 2021. 2021 ;[citado 2024 abr. 30 ] Available from: https://dl.acm.org/doi/pdf/10.1145/3466933.3466984
  • Source: SBSI 2021. Conference titles: XVII Brazilian Symposium on Information Systems. Unidade: EACH

    Assunto: REDES SOCIAIS

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    • ABNT

      MORAIS, Daniel e DIGIAMPIETRI, Luciano Antonio. Methods and Challenges in Social bots Detection: a Systematic Review. 2021, Anais.. Uberlândia: Federal University of Uberlândia, 2021. Disponível em: https://dl.acm.org/doi/pdf/10.1145/3466933.3466973. Acesso em: 30 abr. 2024.
    • APA

      Morais, D., & Digiampietri, L. A. (2021). Methods and Challenges in Social bots Detection: a Systematic Review. In SBSI 2021. Uberlândia: Federal University of Uberlândia. Recuperado de https://dl.acm.org/doi/pdf/10.1145/3466933.3466973
    • NLM

      Morais D, Digiampietri LA. Methods and Challenges in Social bots Detection: a Systematic Review [Internet]. SBSI 2021. 2021 ;[citado 2024 abr. 30 ] Available from: https://dl.acm.org/doi/pdf/10.1145/3466933.3466973
    • Vancouver

      Morais D, Digiampietri LA. Methods and Challenges in Social bots Detection: a Systematic Review [Internet]. SBSI 2021. 2021 ;[citado 2024 abr. 30 ] Available from: https://dl.acm.org/doi/pdf/10.1145/3466933.3466973
  • Source: SBSI 2021. Conference titles: XVII Brazilian Symposium on Information Systems. Unidade: EACH

    Subjects: REDES SOCIAIS, COVID-19

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    • ABNT

      LIRA, Diego Bezerra e XAVIER, Fernando e DIGIAMPIETRI, Luciano Antonio. Combining clustering and classification algorithms for automatic bot detection: a case study on posts about COVID-19. 2021, Anais.. Uberlândia: Federal University of Uberlândia, 2021. Disponível em: https://dl.acm.org/doi/10.1145/3466933.3466970. Acesso em: 30 abr. 2024.
    • APA

      Lira, D. B., Xavier, F., & Digiampietri, L. A. (2021). Combining clustering and classification algorithms for automatic bot detection: a case study on posts about COVID-19. In SBSI 2021. Uberlândia: Federal University of Uberlândia. Recuperado de https://dl.acm.org/doi/10.1145/3466933.3466970
    • NLM

      Lira DB, Xavier F, Digiampietri LA. Combining clustering and classification algorithms for automatic bot detection: a case study on posts about COVID-19 [Internet]. SBSI 2021. 2021 ;[citado 2024 abr. 30 ] Available from: https://dl.acm.org/doi/10.1145/3466933.3466970
    • Vancouver

      Lira DB, Xavier F, Digiampietri LA. Combining clustering and classification algorithms for automatic bot detection: a case study on posts about COVID-19 [Internet]. SBSI 2021. 2021 ;[citado 2024 abr. 30 ] Available from: https://dl.acm.org/doi/10.1145/3466933.3466970

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