Análise de Sentimentos de comentários no YouTube sobre a série Drive to Survive
Resumo
Avaliações de produtos são uma alternativa para validar a opinião popular sobre um produto. A análise de sentimentos é uma tarefa que pode auxiliar nessa tarefa. Este trabalho investiga a expressão de sentimentos em comentários na plataforma YouTube para uma série da Netflix, Drive to Survive, que retrata a vida dos pilotos no contexto da Fórmula 1. Com o uso da API do YouTube, foram coletados 19.404 comentários. Esses textos foram submetidos a uma análise de sentimentos utilizando o algoritmo VADER. Os resultados mostram um desempenho positivo para a série, com 63,1% de comentários positivos. Isso corrobora com pesquisas em outras áreas, indicando o sucesso do conteúdo.
Palavras-chave:
Análise de Sentimentos, VADER, Avaliação de Produto
Referências
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HARTMANN, J. et al. More than a feeling: Accuracy and application of sentiment analysis. International Journal of Research in Marketing, Elsevier, v. 40, n. 1, p. 75–87, 2023.
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LIU, B. Sentiment analysis and opinion mining. [S.l.]: Morgan & Claypool Publishers, 2012. v. 5. 1–167 p. (Synthesis Lectures on Human Language Technologies, 1).
MASSA, F. et al. Massa revela apelo por bortoleto na f1 e cita rusga com piquet sobre 2008: “não quis falar comigo”. ge – Abre Aspas, maio 2025. Entrevista longa concedida na sede da TV Globo em São Paulo.
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NISAR, T.; PRABHAKAR, G. Sports clubs’ use of social media to increase spectator interest. International Journal of Information Management, Elsevier, v. 39, p. 132–138, 2018.
NOVENDRI, R. et al. Sentiment analysis of youtube movie trailer comments using naïve bayes. Bulletin of Computer Science and Electrical Engineering, v. 1, n. 1, p. 26–32, 2020.
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SAMUEL, S.; KÖNIG-RIES, B. Understanding experiments and research practices for reproducibility: an exploratory study. PeerJ, PeerJ Inc., v. 9, p. e11140, 2021.
SHAH, D.; WILLIAMS, A. L. “drive to survive” drives new fans to formula 1? studying viewer experiences of a sports documentary and its influence on the sport’s fandom. Communication & Sport, SAGE Publications Sage CA: Los Angeles, CA, p. 21674795241280209, 2024.
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BÖCKERMAN, T. E. Speed and spectacle: a qualitative case study on fan engagement within a formula one fan community through netflix’s drive to survive. 2024.
CLAVIO, G. Social media and sports. [S.l.]: Human Kinetics Publishers, 2021.
GIANATASIO, D. From Breaking Bad to Lost: The Quality of 13 Famous TV Shows, Charted Over Time. WIRED, 2014. Accessed: 2025-07-14. Disponível em: [link].
HAIDER, S. M.; MAHMOOD, A.; ASLAM, M. N. Vader sentiment analysis without and with english punctuation marks. International Journal of Advanced Trends in Computer Science and Engineering, World Academy of Research in Science and Engineering (WARSE), v. 10, n. 2, p. 1268–1274, 2021. Disponível em: [link].
HARTMANN, J. et al. More than a feeling: Accuracy and application of sentiment analysis. International Journal of Research in Marketing, Elsevier, v. 40, n. 1, p. 75–87, 2023.
HUTTO, C.; VADER, G. E. a parsimonious rule-based model for sentiment analysis of social media text. 2014. DOI: 10.1609/icwsm.v8i1.14550, v. 14550, p. 216–225, 2023.
KUMAR, e. a. Sentiment analysis methods, applications, and challenges: A systematic literature review. Journal of King Saud University - Computer and Information Sciences, Elsevier, v. 36, n. 4, p. 102048, 2024.
LIU, B. Sentiment analysis and opinion mining. [S.l.]: Morgan & Claypool Publishers, 2012. v. 5. 1–167 p. (Synthesis Lectures on Human Language Technologies, 1).
MASSA, F. et al. Massa revela apelo por bortoleto na f1 e cita rusga com piquet sobre 2008: “não quis falar comigo”. ge – Abre Aspas, maio 2025. Entrevista longa concedida na sede da TV Globo em São Paulo.
MEDHAT, W.; HASSAN, A.; KORASHY, H. Sentiment analysis algorithms and applications: A survey. Ain Shams engineering journal, Elsevier, v. 5, n. 4, p. 1093–1113, 2014.
MEDLAND, C. A formula 1 battle for the ages. USA Today, USA Today, p. 05C–05C, 2021.
NISAR, T.; PRABHAKAR, G. Sports clubs’ use of social media to increase spectator interest. International Journal of Information Management, Elsevier, v. 39, p. 132–138, 2018.
NOVENDRI, R. et al. Sentiment analysis of youtube movie trailer comments using naïve bayes. Bulletin of Computer Science and Electrical Engineering, v. 1, n. 1, p. 26–32, 2020.
PALERMO, A.; DELAINE, G. Formula one on social networks: a successful strategy. Zer, v. 28, n. 54, p. 13–29, 2023.
RACHMAD, Y. E. Social Media Impact Theory. [S.l.]: Port Elizabeth Bay Book Publishing, Special Edition, 2023.
RODO, D. J. P. O impacto da série documental formula 1: Drive to survive na renovação de audiência da fórmula 1.
SAMUEL, S.; KÖNIG-RIES, B. Understanding experiments and research practices for reproducibility: an exploratory study. PeerJ, PeerJ Inc., v. 9, p. e11140, 2021.
SHAH, D.; WILLIAMS, A. L. “drive to survive” drives new fans to formula 1? studying viewer experiences of a sports documentary and its influence on the sport’s fandom. Communication & Sport, SAGE Publications Sage CA: Los Angeles, CA, p. 21674795241280209, 2024.
SOBLE, C.; LOWES, M. Narrative storytelling as a fan conversion tool in the netflix docuseries drive to survive. Communication & Sport, SAGE Publications Sage CA: Los Angeles, CA, p. 21674795241238158, 2024.
WANKHADE, M.; RAO, A. C. S.; KULKARNI, C. A survey on sentiment analysis methods, applications, and challenges. Artificial Intelligence Review, v. 55, n. 7, p. 5731–5780, 2022. ISSN 1573-7462. DOI: 10.1007/s10462-022-10144-1.
YOUVAN, D. C. Understanding sentiment analysis with vader: a comprehensive overview and application. AI and Data Science Journal, 2024.
Publicado
12/11/2025
Como Citar
BIANCH, Samuel O. S.; MARTINS, Claudia A.; GOMES, Raphael de S R.; OLIVEIRA, Anderson C. S. de; SILVA, João Gabriel R.; VIEIRA, Vinicius da F..
Análise de Sentimentos de comentários no YouTube sobre a série Drive to Survive. In: ESCOLA REGIONAL DE INFORMÁTICA DE MATO GROSSO (ERI-MT), 14. , 2025, Pontes e Lacerda/MT.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 228-237.
ISSN 2447-5386.
DOI: https://doi.org/10.5753/eri-mt.2025.17218.
