Dergiler / Advances in Hospitality and Tourism Research (AHTR) / 2023 / Cilt: 11 Sayı: 4

Assessing Destination Brand Associations on Twitter: The case of Istanbul

Sayfa
443–475
Yayın Tarihi
2023-12-11
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Based on the study results, a method was proposed for measuring the image of a place brand by observing electronic word of mouth in social media.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:The development of data mining has paved the way for studies that identify brand associations from user-generated content (UGC).
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Temel Bulgular & Veri:In this study, 33,339 English-language tweets containing the word #Istanbul were collected over one year and analyzed using text mining (association rule analysis) and sentiment analysis.
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Sonuç & Katkı:Based on the study results, a method was proposed for measuring the image of a place brand by observing electronic word of mouth in social media.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:association rule · brand concept map · brand image

Abstract

The development of data mining has paved the way for studies that identify brand associations from user-generated content (UGC). However, the number of studies investigating destination associations with social media is limited. The aim of this study is to explore destination associations with UGC on Twitter and to show how data mining and sentiment analysis methods can be applied to destinations to elicit brand associations. In this study, 33,339 English-language tweets containing the word #Istanbul were collected over one year and analyzed using text mining (association rule analysis) and sentiment analysis. As a result of the study, a brand concept map (BCM) of what Twitter users associate with Istanbul was created and compared to other studies that measure associations using conventional methods. The main results show that users have positive associations with tourism in Istanbul. Unique and interesting associations (such as "cats") were observed compared to other previous studies that measured associations to destinations. Based on the study results, a method was proposed for measuring the image of a place brand by observing electronic word of mouth in social media.

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Bu Makaleye Atıf Yap

KASAPOĞLU, C., AKSOY, R., BAŞKOL, M. (2023). Assessing Destination Brand Associations on Twitter: The case of Istanbul. Advances in Hospitality and Tourism Research (AHTR), Cilt: 11 Sayı: 4, 443–475. https://ajindex.com/articles/1021280

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Kaynakça (11)

  1. Aaker, D. (1991). Managing Brand Equity. New York. Aaker, D. A. (1992). The value of brand equity. Journal of Business Strategy, 13(4), 27-32. https://doi.org/10.1108/eb039503
  2. Agrawal, R, Mannila, H., Srikant, R., Toivonen, H., & Verkamo, I. (1996). Fast discovery of association rules. Advances in knowledge discovery and data mining, 12(1), 307-328.
  3. Agrawal, R., & Srikant, R. (1994). Fast algorithms for mining association rules. Proc. of 20th International Conference on Very Large Data Bases, {VLDB’94} (Vol. 1215, pp. 487-499).
  4. Alaei, A. R., Becken, S., & Stantic, B. (2017). Sentiment analysis in tourism: Capitalizing on big data. Journal of Travel Research, 58(2), 175–191. https://doi.org/10.1177/0047287517747753 Alarcón-Urbistondo, P., Rojas-de-Gracia, M. M., & Casado-Molina, A. (2021). Proposal for employing user-generated content as a data source for measuring tourism destination image. Journal of Hospitality & Tourism Research, 10963480211012756. https://doi.org/10.1177/10963480211012756
  5. Alexandris, K., Douka, S., Papadopoulos, P., & Kaltsatou, A. (2008). Testing the role of service quality on the development of brand associations and brand loyalty. Managing Service Quality, 18(3), 239–254. https://doi.org/10.1108/09604520810871865
  6. Alzate, M., Arce-Urriza, M., & Cebollada, J. (2022). Mining the text of online consumer reviews to analyze brand image and brand positioning. Journal of Retailing and Consumer Services, 67, 102989. https://doi.org/10.1016/J.JRETCONSER.2022.102989 Andéhn, M., Kazeminia, A., Lucarelli, A., & Sevin, E. (2014). User-generated place brand equity on Twitter: The dynamics of brand associations in social media. Place Branding and Public Diplomacy, 10(2), 132–144. https://doi.org/10.1057/pb.2014.8
  7. Anderson, J. R., & Bower, G. H. (1980). Human associative memory. Psychology Press. https://doi.org/10.2307/1421672
  8. Baloglu, S., & McCleary, K. W. (1999). A model of destination image formation. Annals of Tourism Research, 26(4), 868–897. https://doi.org/10.1016/S0160-7383(99)00030-4
  9. Başfırıncı, Ç. (2016). Analysing brand image through social network analysis: A research on Turkcell and Vodafone brand. İstanbul Gelişim Üniversitesi Sosyal Bilimler Dergisi, 3(2), 25–50.
  10. Becken, S., Alaei, A. R., & Wang, Y. (2020). Benefits and pitfalls of using tweets to assess destination sentiment. Journal of Hospitality and Tourism Technology, 11(1), 19–34. https://doi.org/10.1108/JHTT-09-2017-0090
  11. Bell, R. C. (2005). The repertory grid technique. In F.