Analysing Customer Engagement of Turkish Airlines Using Big Social Data

Fie Sternberg, Kasper Hedegaard Pedersen, Niklas Klve Ryelund, Raghava Rao Mukkamala, Ravi Vatrapu

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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 data- and 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.
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 data- and 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.
LanguageEnglish
Title of host publicationProceedings of the 7th IEEE International Congress on Big Data : BigData Congress 2018
EditorsShadi Ibrahim, Isaac Triguero, Bingsheng He
Number of pages8
Place of PublicationLos Alamitos, CA
PublisherIEEE
Date2018
Pages74-81
ISBN (Print)9781538672334
ISBN (Electronic)9781538672327
DOIs
StatePublished - 2018
Event7th IEEE International Congress on Big Data. BigData Congress 2018 - San Francisco, United States
Duration: 2 Jul 20187 Jul 2018
Conference number: 7
http://conferences.computer.org/bigdatacongress/2018/

Conference

Conference7th IEEE International Congress on Big Data. BigData Congress 2018
Number7
CountryUnited States
CitySan Francisco
Period02/07/201807/07/2018
Internet address

Bibliographical note

CBS Library does not have access to the material

Keywords

  • Big data
  • Customer satisfaction
  • Data mining
  • Social networking (online)
  • Travel industry
  • Business data
  • Facebook data
  • Turkish Airline ticket
  • Facebook page
  • Big social data
  • Social media
  • Customer engagement
  • Turkish Airlines
  • Facebook
  • Industries
  • Companies
  • Text analytics

Cite this

Sternberg, F., Hedegaard Pedersen, K., Ryelund, N. K., Mukkamala, R. R., & Vatrapu, R. (2018). Analysing Customer Engagement of Turkish Airlines Using Big Social Data. In S. Ibrahim, I. Triguero, & B. He (Eds.), Proceedings of the 7th IEEE International Congress on Big Data: BigData Congress 2018 (pp. 74-81). Los Alamitos, CA: IEEE. DOI: 10.1109/BigDataCongress.2018.00017
Sternberg, Fie ; Hedegaard Pedersen, Kasper ; Ryelund, Niklas Klve ; Mukkamala, Raghava Rao ; Vatrapu, Ravi. / Analysing Customer Engagement of Turkish Airlines Using Big Social Data. Proceedings of the 7th IEEE International Congress on Big Data: BigData Congress 2018. editor / Shadi Ibrahim ; Isaac Triguero ; Bingsheng He. Los Alamitos, CA : IEEE, 2018. pp. 74-81
@inproceedings{ff0b8fb90899421fa5c96ecf65b5532b,
title = "Analysing Customer Engagement of Turkish Airlines Using Big Social Data",
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 data- and 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.",
keywords = "Big data, Customer satisfaction, Data mining, Social networking (online), Travel industry, Business data, Facebook data, Turkish Airline ticket, Facebook page, Big social data, Social media, Customer engagement, Turkish Airlines, Facebook, Industries, Companies, Text analytics, Big data, Customer satisfaction, Data mining, Social networking (online), Travel industry, Business data, Facebook data, Turkish Airline ticket, Facebook page, Big social data, Social media, Customer engagement, Turkish Airlines, Facebook, Industries, Companies, Text analytics",
author = "Fie Sternberg and {Hedegaard Pedersen}, Kasper and Ryelund, {Niklas Klve} and Mukkamala, {Raghava Rao} and Ravi Vatrapu",
note = "CBS Library does not have access to the material",
year = "2018",
doi = "10.1109/BigDataCongress.2018.00017",
language = "English",
isbn = "9781538672334",
pages = "74--81",
editor = "Shadi Ibrahim and Isaac Triguero and Bingsheng He",
booktitle = "Proceedings of the 7th IEEE International Congress on Big Data",
publisher = "IEEE",
address = "United States",

}

Sternberg, F, Hedegaard Pedersen, K, Ryelund, NK, Mukkamala, RR & Vatrapu, R 2018, Analysing Customer Engagement of Turkish Airlines Using Big Social Data. in S Ibrahim, I Triguero & B He (eds), Proceedings of the 7th IEEE International Congress on Big Data: BigData Congress 2018. IEEE, Los Alamitos, CA, pp. 74-81, San Francisco, United States, 02/07/2018. DOI: 10.1109/BigDataCongress.2018.00017

Analysing Customer Engagement of Turkish Airlines Using Big Social Data. / Sternberg, Fie; Hedegaard Pedersen, Kasper; Ryelund, Niklas Klve; Mukkamala, Raghava Rao; Vatrapu, Ravi.

Proceedings of the 7th IEEE International Congress on Big Data: BigData Congress 2018. ed. / Shadi Ibrahim; Isaac Triguero; Bingsheng He. Los Alamitos, CA : IEEE, 2018. p. 74-81.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

TY - GEN

T1 - Analysing Customer Engagement of Turkish Airlines Using Big Social Data

AU - Sternberg,Fie

AU - Hedegaard Pedersen,Kasper

AU - Ryelund,Niklas Klve

AU - Mukkamala,Raghava Rao

AU - Vatrapu,Ravi

N1 - CBS Library does not have access to the material

PY - 2018

Y1 - 2018

N2 - 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 data- and 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.

AB - 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 data- and 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.

KW - Big data

KW - Customer satisfaction

KW - Data mining

KW - Social networking (online)

KW - Travel industry

KW - Business data

KW - Facebook data

KW - Turkish Airline ticket

KW - Facebook page

KW - Big social data

KW - Social media

KW - Customer engagement

KW - Turkish Airlines

KW - Facebook

KW - Industries

KW - Companies

KW - Text analytics

KW - Big data

KW - Customer satisfaction

KW - Data mining

KW - Social networking (online)

KW - Travel industry

KW - Business data

KW - Facebook data

KW - Turkish Airline ticket

KW - Facebook page

KW - Big social data

KW - Social media

KW - Customer engagement

KW - Turkish Airlines

KW - Facebook

KW - Industries

KW - Companies

KW - Text analytics

U2 - 10.1109/BigDataCongress.2018.00017

DO - 10.1109/BigDataCongress.2018.00017

M3 - Article in proceedings

SN - 9781538672334

SP - 74

EP - 81

BT - Proceedings of the 7th IEEE International Congress on Big Data

PB - IEEE

CY - Los Alamitos, CA

ER -

Sternberg F, Hedegaard Pedersen K, Ryelund NK, Mukkamala RR, Vatrapu R. Analysing Customer Engagement of Turkish Airlines Using Big Social Data. In Ibrahim S, Triguero I, He B, editors, Proceedings of the 7th IEEE International Congress on Big Data: BigData Congress 2018. Los Alamitos, CA: IEEE. 2018. p. 74-81. Available from, DOI: 10.1109/BigDataCongress.2018.00017