Sentiment Analysis of the Environmental Impact of Electric Vehicles Using SVM

Fahrul Rizha, Muhammad Arhami, Musta'inul Abdi

Abstract


Transportation is a basic need in everyday life, but the use of fossil fuels in transportation causes serious environmental impacts. Therefore, environmentally friendly alternative fuels such as electric vehicles are a relevant solution. In this context, social media, especially Twitter, becomes a valuable data source for analyzing public sentiment regarding electric vehicles. The IEA (International Energy Agency) notes significant growth in electric vehicle penetration, but the environmental impact of the vehicle's life cycle needs to be considered. Therefore, it is necessary to analyze public opinion sentiment regarding the environmental impact of electric vehicles using the Support Vector Machine (SVM) method. In actual sentiment, positive data was 43.4%, negative 19.4%, and neutral 37.2%. Predicted sentiment shows positive data of 42.6%, negative 14.7%, and neutral. Classification results using SVM with a linear kernel show predominantly positive results with an accuracy of 77%. Based on the accuracy results, on average, the model was able to predict sentiment well by 77%.

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