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

ABSTRACT: 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 this 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 ap

SUBMITTER: Ha S 

PROVIDER: S-EPMC7892356 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature