Twitter Sentiment Analysis of the Low-Cost Airline Services after COVID-19 Outbreak: The Case of AirAsia

Abstract

Background: Public opinion about experience and expectation on services that appear on Twitter platforms provides valuable insights into satisfaction and experience. Objectives: This research investigates consumer perception and opinion toward AirAsia's services after the COVID-19 outbreak. Methods/Approach: A framework is proposed by integrating the customer satisfaction model with the digital service quality dimension: product quality, price, situational factors, personal factors, service quality, and digital service quality. Nvivo is used to extract and analyse Twitter data for sentiment analysis, thematic analysis, and word frequency calculations. Results: Findings demonstrated that AirAsia had received more negative sentiments than positive sentiments, indicating a lower level of satisfaction across all dimensions of customer satisfaction. Conclusions: This research provides the airline industry, especially AirAsia, with an opportunity to better understand the sentiments and preferences of its customers. AirAsia can use the findings of this research to evaluate the quality of their services, especially in terms of service quality, to improve customer satisfaction, gain customer loyalty, and enhance customer experience.