Brazilian Consumer Perceptions of Electric Vehicles Using LLMs on Online Comments
Resumo
The transition from gasoline-powered vehicles to electric vehicles (EVs) is a major step forward, driven by both technological innovations and environmental concerns. This study analyzes the perceptions of Brazilian consumers toward EVs, using a novel dataset of YouTube and Reddit comments collected between 2015 and 2025. To handle the large volume of text, we used the LLaMA 3.2 language model with custom prompts to identify and analyze specific technical aspects of EVs. Our results show that consumers’ main concerns are limited range and high cost, while the most valued aspects are energy efficiency and the technology itself.Referências
Lau, J. H. (2025). Comparative analysis of gasoline and electric vehicles: Economic, environmental, and consumer perspectives. FE - Future Energy Studies.
Oliveira, K., Lunardi, G., and Silva, W. (2025a). Avaliação de sentimentos de aplicativos: Uma comparação entre modelos de linguagem de grande escala. In Anais da XX Escola Regional de Banco de Dados.
Oliveira, K., Lunardi, G., Silva, W., Silveira, T., and Oliveira, A. (2025b). A data augmentation and validation pipeline for improving emotion classification in mobile app reviews. In Anais do XL Simpósio Brasileiro de Bancos de Dados.
Sahoo, P., Singh, A. K., Saha, S., Jain, V., Mondal, S., and Chadha, A. (2024). A systematic survey of prompt engineering in large language models: Techniques and applications.
Sharma, H., Din, F. U., and Ogunleye, B. (2024). Sentiment analysis of electric vehicles using large language models. Analytics.
Soares, T., Costa, R., Soares, E., Calderon, I., Lunardi, G., Valle, P., Guedes, G., and Silva, W. (2025). Machine learning-assisted tools for user experience evaluation: A systematic mapping study. In Anais do XXI Simpósio Brasileiro de Sistemas de Informação, Porto Alegre, RS, Brasil.
Oliveira, K., Lunardi, G., and Silva, W. (2025a). Avaliação de sentimentos de aplicativos: Uma comparação entre modelos de linguagem de grande escala. In Anais da XX Escola Regional de Banco de Dados.
Oliveira, K., Lunardi, G., Silva, W., Silveira, T., and Oliveira, A. (2025b). A data augmentation and validation pipeline for improving emotion classification in mobile app reviews. In Anais do XL Simpósio Brasileiro de Bancos de Dados.
Sahoo, P., Singh, A. K., Saha, S., Jain, V., Mondal, S., and Chadha, A. (2024). A systematic survey of prompt engineering in large language models: Techniques and applications.
Sharma, H., Din, F. U., and Ogunleye, B. (2024). Sentiment analysis of electric vehicles using large language models. Analytics.
Soares, T., Costa, R., Soares, E., Calderon, I., Lunardi, G., Valle, P., Guedes, G., and Silva, W. (2025). Machine learning-assisted tools for user experience evaluation: A systematic mapping study. In Anais do XXI Simpósio Brasileiro de Sistemas de Informação, Porto Alegre, RS, Brasil.
Publicado
12/11/2025
Como Citar
OLIVEIRA, Kalidsa B. de; LUNARDI, Gabriel M.; SILVEIRA, Thiago L. T. da; OLIVEIRA, Adriano Q.; EMMENDORFER, Leonardo Ramos.
Brazilian Consumer Perceptions of Electric Vehicles Using LLMs on Online Comments. In: ESCOLA REGIONAL DE APRENDIZADO DE MÁQUINA E INTELIGÊNCIA ARTIFICIAL DA REGIÃO SUL (ERAMIA-RS), 1. , 2025, Porto Alegre/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 380-383.
DOI: https://doi.org/10.5753/eramiars.2025.16750.
