This summer, our team is assessing the existing electric vehicle (EV) infrastructure in the United States to better understand if it is serving the public properly. To do this, we’re analyzing charging station review data obtained from a popular mobile app that works like a Yelp-like review system for EV charging stations. We are particularly interested in exploring the differences in quality and functioning between public and private charging stations as well as analyzing the different topics of discussion within the reviews and the trends within them. Once we understand how everyday users are interacting with EV charging stations, policy recommendations on infrastructure can be made to effectively support the growing number of electric vehicle owners.
Our project is split into three possible subprojects:
Project 1: Sentiment analysis of reviews.
Here, we are going to use an existing training data set to classify all of the popular mobile app’s EV station reviews by sentiment to discover general sentiment regarding EV charging infrastructure.
Project 2: Categorization of reviews
Next, we are going to categorize all the reviews according to the subjects of the reviews. This will be much more labor intensive because we will need to create a training data set before we can analyze the major concerns of EV users.
Project 3: Predicting station failure
In our final phase, we will analyze real-time data from EV charging stations to create a model to predict when an EV station will break down.
By the end of the summer, we hope to complete all three projects, but we know that we are operating under a strict time constraint, so accomplishing all might not be possible. Despite this, we are excited to tackle all of this this summer!