Topic classification of electric vehicle consumer experiences with transformer-based deep learning

Sooji Ha, Daniel J. Marchetto, Sameer Dharur, Omar I. Asensio
2021 Patterns  
The transportation sector is a major contributor to greenhouse gas (GHG) emissions and is a driver of adverse health effects globally. Increasingly, government policies have promoted the adoption of electric vehicles (EVs) as a solution to mitigate GHG emissions. However, government analysts have failed to fully utilize consumer data in decisions related to charging infrastructure. This is because a large share of EV data is unstructured text, which presents challenges for data discovery. In
more » ... s article, we deploy advances in transformer-based deep learning to discover topics of attention in a nationally representative sample of user reviews. We report classification accuracies greater than 91% (F1 scores of 0.83), outperforming previously leading algorithms in this domain. We describe applications of these deep learning models for public policy analysis and large-scale implementation. This capability can boost intelligence for the EV charging market, which is expected to grow to US$27.6 billion by 2027.
doi:10.1016/j.patter.2020.100195 pmid:33659911 pmcid:PMC7892356 fatcat:q3mx5twztrej7kfjxredgnvok4