A STUDY ON ELECTRIC CARS USING BERTOPIC TOPIC MODELING TECHNIQUE

Today, with the rapid development of technology, the use of environmentally friendly and innovative automobiles continues to increase. Among these automobiles, there is a growing interest in electric vehicles, but it is of great importance for the acceptance of these vehicles to quickly resolve the issues that consumers find inadequate. The rapid increase in the number of potential customers leads to a significant expansion in the volume of data generated and necessitates the use of advanced analytical techniques to process this data effectively. In this context, artificial intelligence and natural language processing (NLP) methods play an important role in the processes of interpreting, classifying and predicting customer data. Innovative methods and applications provide significant economic advantages to businesses in solving problems. The aim of this study is to determine the expectations, concerns, criticisms and complaints of consumers towards electric cars and to provide suggestions to manufacturers and marketers to develop solutions. In the study, BERTopic topic modelling technique was used to determine around which topics customer complaints are concentrated. As a data set, the complaints made to a electric car company between 1 January 2024 and 1 January 2025 were classified and analysed. The findings obtained can contribute to businesses to better meet customer expectations for electric cars and positively influence their purchasing behaviour.