Impact of eWoM (Electronic Word of Mouth) on Consumer Purchasing Decisions in the International Airline Industry

The growing competition in the international airline industry justifies the importance of extensive marketing communications for attracting consumers' attention. One of the promising methods in marketing research is a sentiment analysis (opinion mining). This study aims to reveal how opinion mining of Twitter data may enrich airline companies' marketing analytics. To research the topic, R programming language was used to extract and clean unstructured data from Twitter and conduct sentiment analysis. Event study enabled to identify dates when sentimen shifts occured and find what caused them. Then, these trigger events were classified and a final conclusion on what most affects a choice of air travelers was made. This enabled to develop an algorithm for evaluating Twitter-expressed opinions of airlines' customers. It is expected that this method will be of use for marketing departments of airline companies, consumers, and marketing researchers.