Sentiment analysis of customer engagement on social media in transport online

Currently, social media are commonly used by business organizations to get many advantages. Through social media, business gets feedback from their customer by giving them a room for sharing opinion or comment. This kind of customer engagement became a tool of marketing and promotion. This research proposes investigating the customer engagement by analysis the comments on social media (Facebook and Twitter) in transport online. This study investigates by mining the comments of fan page Facebook and tweet of Twitter in three transports online in Indonesia; Gojek, Grab, and Uber using the API service which is provided both of social media. The data comments are classified into some categories, positive, negative, and neutral sentiment using TF-IDF. The result shows that the category "Feedback system by driver" and "Feedback system by user" have the most comments for three means of transports online, while category "Service quality for driver" has the smallest comments. The study also reveals that the most comments are complaining. This feedback of social media can be used to evaluate the performance of these business transport online.