Travelers' perception of smart airport facilities: An X (Twitter) sentiment analysis

This study investigates travelers' perceptions of smart airport facilities through sentiment analysis. It collected 39,616 comments from thirteen smart airports, and 25,572 tweets were analyzed. Most mentioned words about the smart airport included "technology" and "security". Comments also highlighted concerns about airport customer service, including "bag," "transit," and "disabled." The results also reveal that travelers are more concerned about the outcome of these facilities, such as the efficiency and time management of flights via smart facilities. The most mentioned words in the tweets related to smart airport operations are "flight," "waiting," and "time". Despite most smart facilities being equipped in the airports aiming to raise travelers' satisfaction, the results showed that 12 smart airports' tweets were generally neutral. Smart airport facilities might not add as much value to the airport impression as we expect. Brisbane International Airport was the only one with a positive perception of smart airport facilities. Most travelers mentioned that the airport had faster and better wifi and the airport is continuously improving. In contrast, Charles de Gaulle Airport and London Heathrow Airport had the highest percentage of negative sentiment, with 25.90% and 27.52% of tweets being negative, respectively. Travelers' complained that self-check-in kiosks were a mess, unhelpful staff and poor wifi. The results reveal travelers' concerns regarding smart airport facilities, and they let us know the importance of smart facility management. Smart airport facilities were initially designed to shorten travelers' time and enhance satisfaction, yet unhelpful staff and poor managed kiosks raise dissatisfaction. This study helps airport managers and operators to address the weakest part of smart airports as reflected in social media comments. It also fills the academic voids in examining travelers' satisfaction with smart facilities using social media and sentiment analysis via artificial intelligence.