The Identification of Marketing Performance Using Text Mining of Airline Review Data

• Published in: Mobile information systems Vol. 2019; no. 2019; pp. 1 - 8
• Main Authors: Hong, Jae-Won, Park, Seung-Bae
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 01.01.2019; Hindawi; Hindawi Limited
• Subjects: Airlines; Automation; Aviation; Big Data; Communication; Consumers; Content analysis; Data analysis; Data mining; End users; Environmental scanning; Industrial development; Keywords; Marketing; Methods; Product reviews; R&D; Research & development; Researchers; Semantics; Social network analysis; Social networks; Social research; Text analysis; Word of mouth advertising
• ISSN: 1574-017X; 1875-905X
• DOI: 10.1155/2019/1790429

We are aim firstly to extract major keywords using text mining method, secondly to identify prominent keyword from the keywords extracted from text mining analysis, and then to confirm differences in influences of the keywords which affect corporate performance. Results were as following. First, keywords have been found to show distinctive features. Since the keywords posted from the clients showed certain tendency, airlines accordingly need service management by identifying the service property through keyword analysis. Second, prominent keywords have been found out of the keyword extracted from text mining. Some of the keywords have significantly correlated with marketing performance, but others not. This implies that the company could uncover consumers’ needs through the prominent keywords and managing the properties related to the prominent keywords would help with improving corporate performance. Third, “recommend” should be treated distinctively with “satisfaction” in terms of service management through the keywords. Results suggest strategic implications to the practical business environment by analyzing keywords around the industry using text mining. We believe this work, which aims to establish common ground for understanding these analyses across multiple disciplinary perspectives, will encourage further research and development of service industry.