소셜미디어 빅데이터를 활용한 항공사 이미지 변화 분석 = K항공의 램프리턴을 중심으로

다국어 초록 (Multilingual Abstract)

To survive keen competition, its necessary for corporations to build good corporate images for consumers. The purpose of this study is to suggest some implications to improve and enhance corporate image after a negative incident. This study is focused on the image difference through big data analysis of “K” airline before and after a ramp return. The big data were collected by text mining, co-occurrence frequency analysis, and semantic network analysis and then analyzed. The results are as follows. First, the amount of data increased steeply after the incident, which could significantly affect public image formation or recognition. Second, most of the data about “K” airline were related to flight routes and schedules, cabin crews, and recruiting before the incident. The airline was presented as a socially responsible and ethical corporation. On the other hand, after the incident most of the data collected contained words displaying a negative representation of executives. Third, through ego network analysis, central images of people associated with the airline before the incident were crew, but after they were executives who were related to the crisis. The results show that after the incident, the data presented negative images about “K” airline. More than anything, in the companys crisis management communications the management of people associated with the incident is important. Finally, some implications for crisis management are provided.