Skip to main content

A Review on Exploiting Social Media Analytics for the Growth of Tourism

  • Conference paper
  • First Online:
Recent Trends in Data Science and Soft Computing (IRICT 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 843))

Abstract

Advances in technology has led to absolutely novel and creative areas for its applications. The popularity of social media has seen the stunning growth of user-generated content that could be potentially useful but yet under-utilized. Analysis of the social media data could produce valuable insights for corporations by performing data analytics on consumer behaviours and predict the market trend. In the recent years, tourism is one of the fastest growing sector in the world and United Arab Emirates (UAE) is deemed as one of the popular travel destination worldwide. This paper focuses to view the growth of tourism sector in UAE, its potential and avenue for growth in the future and most importantly the utilization of technology to contribute to business improvement. It discusses about how social media analytics can improve the competitiveness in tourism and hospitality industry in UAE by discussing the technologies used for social media analytics. It recommends to employ social media analytics for the opportunities it provides towards business improvement as the utilization of analytics can be a turn-around factor to improve business performance.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Obar, J.A., Wildman, S.: Social media definition and the governance challenge. An introduction to the special issue. Telecommun. Policy 39(9), 745–750 (2015)

    Article  Google Scholar 

  2. Perrin, A.: Social Media Usage: 2005–2015. Pew Research Center (2015)

    Google Scholar 

  3. Mauro, A.D., Greco, M., Grimaldi, M.: A formal definition of Big Data based on its essential features. Libr. Rev. 65(3), 122–135 (2016)

    Article  Google Scholar 

  4. Del Vecchio, P., Mele, G., Ndou, V., Secundo, G.: Creating value from Social Big Data: Implications for Smart Tourism Destinations. Information Processing & Management (2017)

    Google Scholar 

  5. World Travel & Tourism Council: Global Travel & Tourism Benchmarking Report (2017)

    Google Scholar 

  6. Turner, R., Freiermuth, E.: Travel and Tourism: Economic Impact 2017 United Arab Emirates. World Travel & Tourism Council, London (2017)

    Google Scholar 

  7. Koo, C., Ricci, F., Cobanoglu, C., Okumus, F.: Special issue on smart, connected hospitality and tourism. Inf. Syst. 19(4), 699–703 (2017)

    Google Scholar 

  8. Hoteliermiddleeastcom, News Analysis: UAE and Saudi Arabia’s hotel investments, Dubai, pp. 1–4 (2017)

    Google Scholar 

  9. Alsumairi, M., HongTsui, K.W.: A case study: the impact of low-cost carriers on inbound tourism of Saudi Arabia. J. Air Transp. Manag. 62, 129–145 (2017)

    Article  Google Scholar 

  10. Crescent Rating: MasterCard-CrescentRating Global Muslim Travel Index 2017. https://www.crescentrating.com/reports/mastercard-crescentrating-global-muslim-travel-index-gmti-2017.html. Accessed 6 Feb 2018

  11. Mohsin, A., Ramli, N., Alkhulayfi, B.A.: Halal tourism: emerging opportunities. Tour. Manag. Perspect. 19, 137–143 (2016)

    Article  Google Scholar 

  12. Mujtaba, U.S.: Ramadan: the month of fasting for Muslims, and tourism studies—mapping the unexplored connection. Tour. Manag. Perspect. 19, 170–177 (2016)

    Article  Google Scholar 

  13. Sharma, P., Paulsingh, B.S.: Evolution of social media marketing. Int. J. Adv. Res. Comput. Commun. Eng. 6(3), 147–151 (2017)

    Article  Google Scholar 

  14. Chen, D.W., Tabari, S.: A study of negative customer online reviews and managerial responses on social media—case study of the Marriott Hotel Group in Beijing. J. Consum. Mark. 41, 53–64 (2017)

    Google Scholar 

  15. Brandt, T., Bendler, J., Neumann, D.: Social media analytics and value creation in urban smart tourism ecosystems. Inf. Manag. 54(6), 703–713 (2017)

    Article  Google Scholar 

  16. Miah, S.J., Vu, H.Q., Gammack, J., McGrath, M.: A big data analytics method for tourist behaviour analysis. Inf. Manag. 54(6), 771–785 (2017)

    Article  Google Scholar 

  17. Stieglitz, S., Mirbabaie, M., Ross, B., Neuberger, C.: Social media analytics: challenges in topic discovery, data collection, and data preparation. Int. J. Inf. Manag. 39, 156–168 (2018)

    Article  Google Scholar 

  18. Abrons, R.: The disadvantages of using social networks as marketing tools. http://smallbusiness.chron.com/disadvantages-using-social-networks-marketing-tools-20861.html. Accessed 27 Jan 2018

  19. Indurkhya, N., Damerau, F.J.: Handbook of natural language processing, 2nd edn. Taylor and Francis Group, LLC, London (2010)

    Google Scholar 

  20. Tsirakis, N., Poulopoulos, V., Tsantilas, P., Varlamis, I.: Large scale opinion mining for social, news and blog data. J. Syst. Softw. 127, 237–248 (2017)

    Article  Google Scholar 

  21. Mäntylä, M.V., Graziotin, D., Kuutila, M.: The evolution of sentiment analysis: a review of research topics, venues, and top cited papers. Comput. Sci. Rev. 27, 16–32 (2016)

    Article  Google Scholar 

  22. Vyas, V., Uma, V.: An extensive study of sentiment analysis tools and binary classification of tweets using rapid miner. Procedia Comput. Sci. 125, 329–335 (2018)

    Article  Google Scholar 

  23. Cajachahua, L., Burga, I.: Sentiments and opinions from Twitter about Peruvian touristic places using correspondence analysis. CEUR Workshop Proc. 2029, 178–189 (2017)

    Google Scholar 

  24. Doğan, Y., Turdu, Y.: Discovering similar cities using text mining: a recommendation application for Turkey. Int. J. Eng. Sci. 1(12), 8–14 (2017)

    Google Scholar 

  25. Minazzi, R.: Social Media Marketing in Tourism and Hospitality. Springer, New York (2015)

    Book  Google Scholar 

  26. Sanz-Blaz, S., Buzova, D.: Guided tour influence on cruise tourist experience in a port of call: an eWOM and questionnaire-based approach. Int. J. Tourism Res. 18(6), 558–566 (2016)

    Google Scholar 

  27. Garant, A.: Social Media Competitive Analysis and Text Mining: A Case Study in Digital Marketing in the Hospitality Industry. Aalto University Library, Helsinki (2017)

    Google Scholar 

  28. Marcos, E., DeCastro, V., MartínPeña, M.L., Garrido, E.D., Lopez-sanz, M., ManuelVara, J.: Education on service science management and engineering. Exploring services science. In: Lecture Notes in Business Information Processing Book Series, vol. 201, pp. 264–277 (2015)

    Google Scholar 

  29. Alcoba, J., Mostajo, S., Paras, R., Mejia, G.C., Ebron, R.A.: Framing Meaningful Experiences Toward a Service Science-Based Tourism Experience Design, pp. 129–140. Springer, Cham (2016)

    Google Scholar 

  30. Morgan, J.: Destination ambassadors: examining how hospitality companies value brand ambassadorship from front-line employees: a case study of four seasons hotels and resorts destination ambassadors: examining how hospitality companies value brand ambassadorship. McMaster J. Commun. 11, 237–262 (2014)

    Google Scholar 

  31. Krengel, L.: The financial impact of joining the chain and improving hotel rating: a case study in Russia. Open J. Bus. Manag. 4(4), 659–674 (2016)

    Article  Google Scholar 

  32. Sun, S., Luo, C., Chen, J.: A review of natural language processing techniques for opinion mining systems. Inf. Fus. 36, 10–25 (2017)

    Article  Google Scholar 

  33. Kang, M., Ahn, J., Lee, K.: Opinion mining using ensemble text hidden Markov models for text classification. Expert Syst. Appl. 94, 218–227 (2018)

    Article  Google Scholar 

  34. Bucur, C.: Using opinion mining techniques in tourism. Procedia Econ. Finance 23, 1666–1673 (2015)

    Article  Google Scholar 

  35. Tjahyanto, A., Sisephaputra, B.: The utilization of filter on object-based opinion mining in tourism product reviews. Procedia Comput. Sci. 124, 38–45 (2017)

    Article  Google Scholar 

  36. Sift Analytics Group Pte Ltd, Social Media Analytics. http://www.sift-ag.com/ms-en/products-solutions/predictive-analytics/social-media-analytics. Accessed 17 May 2018

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Preethi Subramanian .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yan, L.X., Subramanian, P. (2019). A Review on Exploiting Social Media Analytics for the Growth of Tourism. In: Saeed, F., Gazem, N., Mohammed, F., Busalim, A. (eds) Recent Trends in Data Science and Soft Computing. IRICT 2018. Advances in Intelligent Systems and Computing, vol 843. Springer, Cham. https://doi.org/10.1007/978-3-319-99007-1_32

Download citation

Publish with us

Policies and ethics