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DEPREM ZAMANINDAKİ GSM OPERATÖRLERİNE İLİŞKİN TÜKETİCİ ALGILARININ SOSYAL MEDYA PAYLAŞIMLARINDA ARAŞTIRILMASI

Year 2024, Volume: 15 Issue: 1 -Deprem Özel Sayısı-, 544 - 570, 22.02.2024
https://doi.org/10.54688/ayd.1372546

Abstract

Bu çalışmanın amacı 6 Şubat Depremi olarak da bilinen Kahramanmaraş (Pazarcık) Depremi sonrasında GSM operatörlerinin sağladığı hizmetle alakalı sosyal medya kullanıcı yorumlarının konu modellemesi ve duygu analiziyle incelenmesidir. Araştırmanın verileri ilgili konuda yayınlanan ve en çok yorum alan üç videoda yer alan kullanıcı yorumlarından oluşmaktadır. Çalışmanın sonucunda oluşturulan konu başlıkları içerdiği kelimelere göre sınıflandırılmış ve konular içinde en çok tekrar eden kelime frekansları çok kriterli karar verme problemlerinde kullanılan ABC yöntemiyle sıralanmıştır. Böylelikle modellenen konuların (bir anlamda YouTube kullanıcıları nezdinde öne çıkan problemlerin) önem sırası saptanmıştır. Ek olarak gerçekleştirilen duygu analizi sonrasında GSM operatörleriyle alakalı negatif duyguların pozitif duygulardan daha fazla olduğu tespit edilmiştir. Konu modellerine bakıldığında genel olarak sağlanan hizmetlerin yetersizliğinden, reklâmlarda verilen vaatleri yerine getirilmemesinden ve düzeltilmesi yönündeki umutlarından bahsedildiği görülmüştür. Çalışmanın sonuçları büyük felaketlerde GSM operatörlerinin etkinliğine vurgu yapmaktadır ve çalışmanın ileride yapılabilecek metin analitiği temelli multidisipliner çalışmalara rehberlik edeceği düşünülmektedir.

Ethical Statement

Araştırmanın hazırlanmasında etik kurallara uygunluk sağladığımı beyan ederim. Araştırma verilerinin kullanımında da herhangi bir şekilde etik kurul izin belgesi gerekmemektedir.

Supporting Institution

Araştırma herhangi bir kurum tarafından desteklenmemiştir.

References

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INVESTIGATING CONSUMER PERCEPTIONS OF GSM OPERATORS AT THE TIME OF EARTHQUAKE ON SOCIAL MEDIA POSTS

Year 2024, Volume: 15 Issue: 1 -Deprem Özel Sayısı-, 544 - 570, 22.02.2024
https://doi.org/10.54688/ayd.1372546

Abstract

This study aims to examine the social media user comments related to the service provided by GSM operators after the Kahramanmaraş (Pazarcık) Earthquake, also known as the 6 February Earthquake, via topic modelling and sentiment analysis. The data of the study consists of user comments in the three videos published on the relevant topic and receiving the most comments. The topics created as a result of the study were classified according to the words they contain and the most recurring word frequencies within the topics were ranked using the ABC method used in multi-criteria decision making problems. Thus, the order of importance of the modelled topics (i.e. the prominent problems for YouTube users) was determined. In addition, after the sentiment analysis, it was determined that negative sentiments related to GSM operators were higher than positive sentiments. When the topic models are examined, it is seen that the inadequacy of the services provided, the failure to fulfil the promises made in the advertisements and the hopes for correction are generally mentioned. The results of the study emphasise the effectiveness of GSM operators in major disasters and it is thought that the study will guide future text analytics-based multidisciplinary studies.

References

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  • Ahn, J., Son, H., & Chung, A. D. (2021). Understanding public engagement on twitter using topic modeling: The 2019 Ridgecrest earthquake case. International Journal of Information Management Data Insights, 1(2), 100033.
  • Akın, M. (2016). Impact of brand experience built by gsm operators in turkey on young consumers’ brand loyalty. International Review of Management and Business Research, 5(2), 438-450.
  • Aksoy, E., Akgün, E., Softa, M., Koçbulut, F., Sözbi̇li̇r, H., Tatar, O., & Erol, S. Ç. (2023). 6 Şubat 2023 Pazarcık (Kahramanmaraş) depreminin Doğu Anadolu Fay Zonu Erkenek ve Pazarcık segmentleri üzerindeki etkisi: Çelikhan-Gölbaşı (Adıyaman) Arasından Gözlemler. Türk Deprem Araştırma Dergisi, 5(1), 85-104.
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  • Erdi̇n, H. E., Çeli̇k, H. Z., Aydin, M. B. S., & Parti̇göç, N. S. (2023). Afet ve acil durumlarda sosyal altyapı alanlarının toplanma alanı olarak belirlenme kriterleri ve yöntemi. Türk Deprem Araştırma Dergisi, 5(1), 1-21.
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  • Hatefi, S. M., Torabi, S. A., & Bagheri, P. (2014). Multi-criteria ABC inventory classification with mixed quantitative and qualitative criteria. International Journal of Production Research, 52(3), 776-786.
  • Huang L., Ma J., & Chen C. (2017). Topic detection from microblogs using t-lda and perplexity. 24 th Asia-Pacific Software Software Engineering Conference Workshops (APSECW). (pp. 71-77). Nanjing-China.
  • ITU, 2023. Commited to Connecting the World-Statistics, Erişim adresi: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx
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  • Kızgın, Y., & Benli, T. (2013). The examining of gsm operators’ customer complaint management (ccm) applications in Turkey with discriminant analysis. International Journal of Business and Management, 8(3), 1-17.
  • Kobayashi, H. (2014). Perplexity on reduced corpora. 52nd Annual Meeting of the Association for Computational Linguistics. (pp. 797-806). Baltimore, MD.
  • Koenig, N. (2023). Topic modeling company reviews with lda. 20 Eylül 2023, https://nkoenig06.github.io/gd-tm-lda.html.
  • Koksal A. (2023). Turkish Sentiment Analysis model is a fine-tuned checkpoint of pretrained BERTurk model 128k uncased with BounTi dataset. 30 Eylül 2023, https://huggingface.co/akoksal/bounti
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  • Kumar, V., Leszkiewicz, A., & Herbst, A. (2018). Are you back for good or still shopping around? investigating customers’ repeat churn behavior. Journal of Marketing Research, 55(2), 208-225.
  • Kurnia, P. F. & Suharjito. (2018). Business intelligence model to analyze social media information. Procedia Computer Science, 135, 5-14.
  • Kyei, D. A., & Bayoh, A. T. M. (2017). Innovation and Customer Retention in the Ghanaian telecommunication industry. International Journal of Innovation, 5(2), 171-183.
  • Laleoğlu B. 2023. Verilerle 6 Şubat Depremleri ve Özellikleri, Erişim adresi: https://www.setav.org/verilerle-6-subat-depremleri-ve-ozellikleri/
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  • Maden, S. (2023). 6 Şubat 2023’te Kahramanmaraş’ta yaşanan depremler ekseninde Türkiye’de deprem haberciliğine bakış: Prof. Dr. Süleyman İrvan ile Söyleşi. Etkileşim, 6(11), 406-420.
  • Mano, R. M., Kirshcenbaum, A., & Rapaport, C. (2019). Earthquake preparedness: A Social Media Fit perspective to accessing and disseminating earthquake information. International Journal of Disaster Risk Management, 1(2), 19-31.
  • Meral, A. B., & Baş, M. (2013). Türkiye’de Faaliyet gösteren gsm operatörlerinin hizmet kalitesi bakımından karşılaştırılması ve uygulanan rekabet stratejileri. Gazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 15(2), 41-70.
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  • Omar, M., On, B.-W., Lee, I., & Choi, G. S. (2015). LDA topics: Representation and evaluation. Journal of Information Science, 41(5), 662-675.
  • Osatuyi, B. (2013). Information sharing on social media sites. Computers in Human Behavior, 29(6), 2622-2631.
  • Pavlinek, M., & Podgorelec, V. (2017). Text classification method based on self-training and LDA topic models. Expert Systems with Applications, 80, 83-93.
  • Phadke, M., Bhattacharya, A., Shethia, M., & Shah, S. (2022). Feedback based telecom churn prediction using machine learning. 2022 5th International Conference on Advances in Science and Technology (ICAST), 481-485. https://doi.org/10.1109/ICAST55766.2022.10039530
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There are 63 citations in total.

Details

Primary Language Turkish
Subjects Business Administration, Business Systems in Context (Other)
Journal Section Special Issue :Earthquake
Authors

Murat Fatih Tuna 0000-0002-8634-8643

Publication Date February 22, 2024
Submission Date October 7, 2023
Published in Issue Year 2024 Volume: 15 Issue: 1 -Deprem Özel Sayısı-

Cite

APA Tuna, M. F. (2024). DEPREM ZAMANINDAKİ GSM OPERATÖRLERİNE İLİŞKİN TÜKETİCİ ALGILARININ SOSYAL MEDYA PAYLAŞIMLARINDA ARAŞTIRILMASI. Akademik Yaklaşımlar Dergisi, 15(1 -Deprem Özel Sayısı-), 544-570. https://doi.org/10.54688/ayd.1372546