Fie Sternberg, Kasper Hedegaard Pedersen, Niklas Klve Ryelund, R. Mukkamala, Ravikiran Vatrapu
{"title":"Analysing Customer Engagement of Turkish Airlines Using Big Social Data","authors":"Fie Sternberg, Kasper Hedegaard Pedersen, Niklas Klve Ryelund, R. Mukkamala, Ravikiran Vatrapu","doi":"10.1109/BigDataCongress.2018.00017","DOIUrl":null,"url":null,"abstract":"Companies started taking advantage of the unlocked potential of Big Social Data, however, research on airlines’ use of social media is limited. This research aims to investigate to what extent Turkish Airlines can utilize their Facebook page to improve performance metrics. This study will exploit the concepts of Big Social Data, customer satisfaction, sentiment analysis to answer the research questions by employing dataand text mining, machine learning. The results showed a weak relationship between the business data and Facebook data, however, the findings provided explanations to customer behavior and showed that most of the company’s Facebook users were likely to purchase a Turkish Airline ticket. Therefore, Turkish Airlines could utilize their Facebook page in the short-term to improve revenue-generating indicators such as customer satisfaction and likelihood of purchase.","PeriodicalId":177250,"journal":{"name":"2018 IEEE International Congress on Big Data (BigData Congress)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Congress on Big Data (BigData Congress)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BigDataCongress.2018.00017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
Companies started taking advantage of the unlocked potential of Big Social Data, however, research on airlines’ use of social media is limited. This research aims to investigate to what extent Turkish Airlines can utilize their Facebook page to improve performance metrics. This study will exploit the concepts of Big Social Data, customer satisfaction, sentiment analysis to answer the research questions by employing dataand text mining, machine learning. The results showed a weak relationship between the business data and Facebook data, however, the findings provided explanations to customer behavior and showed that most of the company’s Facebook users were likely to purchase a Turkish Airline ticket. Therefore, Turkish Airlines could utilize their Facebook page in the short-term to improve revenue-generating indicators such as customer satisfaction and likelihood of purchase.