Research Article
BibTex RIS Cite

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

Murat Fatih Tuna

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.

Keywords

6 Şubat Depremi GSM operatörleri Konu modellemesi YouTube kullanıcıları Tüketici algıları

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

  • AFAD. (2023a). Basın Bülteni-Kahramanmaraş’ta Meydana Gelen Depremler HK. ˗ 34. 15 Eylül 2023, https://www.afad.gov.tr/kahramanmarasta-meydana-gelen-depremler-hk-34.
  • AFAD. (2023b). 6 Şubat Deprem Bölgesindeki Aktivite Haritası. 15 Eylül 2023, https://twitter.com/DepremDairesi/status/1628044504061157377/photo/1.
  • 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.
  • Alghamdi, R., & Alfaqi, K. (2015). A survey of topic modeling in text mining. International Journal of Advanced Computer Science and Applications, 6(1), 147-153.
  • Almuqren, L., & Cristea, A. (2021). AraCust: A Saudi Telecom Tweets corpus for sentiment analysis. PeerJ Computer Science, 7, e510.
  • BTK. (2022). Türkiye Elektronik Haberleşme Sektörü Üç Aylık Pazar Verileri. 12 Eylül 2023, https://www.btk.gov.tr/uploads/pages/pazar-verileri/2022-q3.pdf
  • Chae, J., Thom, D., Bosch, H., Jang, Y., Maciejewski, R., Ebert, D. S., & Ertl, T. (2012). Spatiotemporal social media analytics for abnormal event detection and examination using seasonal-trend decomposition. 2012 IEEE conference on visual analytics science and technology (VAST). (pp. 143-152). Seatle, WA.
  • Corte, V. D., Iavazzi, A., & D’Andrea, C. (2015). Customer involvement through social media: The cases of some telecommunication firms. Journal of Open Innovation: Technology, Market, and Complexity, 1(1), 1-10.
  • Cui, W., Wu, Y., Liu, S., Wei, F., Zhou, M. X., & Qu, H. (2010). Context preserving dynamic word cloud visualization. 2010 IEEE Pacific Visualization Symposium (PacificVis) (pp. 121-128). Taipei, Taiwan.
  • Dasgupta, K., Singh, R., Viswanathan, B., Chakraborty, D., Mukherjea, S., Nanavati, A. A., & Joshi, A. (2008). Social ties and their relevance to churn in mobile telecom networks. Proceedings of the 11th international conference on Extending database technology: Advances in database technology. (pp. 668-677). Nantes, France.
  • Du, H. S., Ke, X., He, W., Chu, S. K. W., & Wagner, C. (2019). Achieving mobile social media popularity to enhance customer acquisition: Cases from P2P lending firms. Internet Research, 29(6), 1386-1409.
  • 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.
  • Evans, D. (2010). Social Media Marketing: The Next Generation of Business Engagement. John Wiley & Sons. Flores, B. E., & Clay Whybark, D. (1986). Multiple criteria ABC analysis. International Journal of Operations & Production Management, 6(3), 38-46.
  • Gürboğa, Ş., Gökçe, O., Mustafa, V., & Tüfekçi, K. (2016). Türkiye’de yüzey faylanması tehlikesinin değerlendirilmesi ve fay sakınım bantlarının oluşturulması. Doğal Kaynaklar ve Ekonomi Bülteni, 21, 29-45.
  • Güven Z. A., Diri B., & Çakaloğlu T. (2019). Comparison of topic modeling methods for type detection of turkish news. International Conference on Computer Science and Engineering (UBMK). (pp. 150-154). Samsun, Türkiye.
  • 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
  • Kızgın, Y. (2008). Genç Gsm abonelerinin operatör seçimlerini etkileyen değişkenlerin konumlandırılması üzerine bir alan araştırması: Muğla Üniversitesi öğrencileri örneği. Journal of Management and Economics Research, 6(10), 142 - 161,.
  • 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
  • Kostić, S. M., Simić, M. I., & Kostić, M. V. (2020). Social network analysis and churn prediction in telecommunications using graph theory. Entropy, 22(7), 1-23.
  • 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/
  • Li, J., Wang, J., Xu, N., Hu, Y., & Cui, C. (2018). Importance degree research of safety risk management processes of urban rail transit based on text mining method. Information, 9(2), 26.
  • 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.
  • O’Callaghan, D., Greene, D., Carthy, J., & Cunningham, P. (2015). An analysis of the coherence of descriptors in topic modeling. Expert Systems with Applications, 42(13), 5645-5657.
  • 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
  • Polatgil, M. (2023a). Analyzing comments made to the duolingo mobile application with topic modeling. International Journal of Computing and Digital Systems, 13(1), 223-230.
  • Polatgil, M. (2023b). TOGG otomobili için youtube yorumlarının konu modellemesi. International Marmara Social Sciences Congress (Imascon Spring). (pp.48-53). Kocaeli-Turkey.
  • Ran, Y. (2011). Considerations and suggestions on improvement of communication network disaster countermeasures after the wenchuan earthquake. IEEE Communications Magazine, 49(1), 44-47.
  • Ranjan, S., Sood, S., & Verma, V. (2018). twitter sentiment analysis of real-time customer experience feedback for predicting growth of indian telecom companies. 2018 4th International Conference on Computing Sciences (ICCS), 166-174.
  • Resch, B., Usländer, F., & Havas, C. (2018). Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment. Cartography and Geographic Information Science, 45(4), 362-376.
  • Ribeiro, H., Barbosa, B., Moreira, A. C., & Rodrigues, R. G. (2023). Determinants of churn in telecommunication services: A systematic literature review. Management Review Quarterly, 1-38.
  • Saldaña, M. (2022). Who is to blame? analysis of government and news media frames during the 2014 earthquake in Chile. Journalism Studies, 23(1), 25-47.
  • Şengün, H. İ., & Menteş, N. (2018). GSM Operatör markalarının tüketici açısından değerlendirilmesi. Mukaddime, 9(1), 209-228.
  • Shaw, R., Shiwaku Hirohide Kobayashi, K., & Kobayashi, M. (2004). Linking experience, education, perception and earthquake preparedness. Disaster Prevention and Management: An International Journal, 13(1), 39-49.
  • Smith, A., Hawes, T., & Myers, M. (2014). Hiearchie: visualization for hierarchical topic models. proceedings of the workshop on interactive language learning, Visualization, and Interfaces, 71-78.
  • STATISTA. (2022). Telecommunications Infrastructure & Equipment - Statistics & Facts. 12 Eylül 2023, https://www.statista.com/topics/2844/telecommunications-equipment/
  • STATISTA. (2023). Telecommunications Services - Statistics & Facts. 12 Eylül 2023, https://www.statista.com/topics/2665/telecommunications-services/
  • Sunny, E.-E., & Abolaji, O. S. (2016). Electronic customer relationship management (e-crm) & marketing performance: empirical evidence from nigeria telecom sector. Journal of Economics, Management and Trade, 11(1), 1-14.
  • Susanti, A. R., Djatna, T., & Kusuma, W. A. (2017). Twitter’s Sentiment Analysis on Gsm Services using Multinomial Naïve Bayes. TELKOMNIKA (Telecommunication Computing Electronics and Control), 15(3), 1354-1361.
  • Tetik N., & Albulut, İ. İ. (2023). 6 şubat 2023’te yaşanan depremin ekonomik ve finansal etkileri: ihracat üzerinden bir inceleme, İçinde M. Öztürk ve M. Kırca (Ed.), Kahramanmaraş merkezli depremler sonrası için akademik öneriler (ss. 93-103). 1000 Kitap.
  • Tundjungsari, V. (2013). Business intelligence with social media and data mining to support customer satisfaction in telecommunication industry. International Journal of Computer Science and Electronics Engineering (IJCSEE), 1(1), 61-64.
  • TÜRK TELEKOM. (2023). Deprem Bölgelerimizdeki Ücretsiz Mobil Araç ve WiFi Noktalarımız. 8 Eylül 2023, https://www.turktelekom.com.tr/tt-hakkimizda/duyurular/Sayfalar/deprem-bolgelerimizdeki-ucretsiz-wifi-noktalarimiz.aspx
  • TURKCELL. (2023). Afetle Mücadele. 8 Eylül 2023, https://www.turkcell.com.tr/tr/hakkimizda/kurumsal-iletisim/sosyal-sorumluluk/afetle-mucadele
  • Vakulenko, S., Müller, O., & vom Brocke, J. (2014). Enriching itunes app store categories via topic modeling. building a better world through information systems. The 5th International Conference on Information Systems (pp. 1-11). Auckland-New Zealand.
  • Vidya, N. A., Fanany, M. I., & Budi, I. (2015). Twitter sentiment to analyze net brand reputation of mobile phone providers. Procedia Computer Science, 72, 519-526.
  • VODAFONE. (2023). Afet Bilgilendirme. 8 Eylül 2023, https://www.vodafone.com.tr/afet-bilgilendirme.
  • Wang, D., Wang, P., Liu, K., Zhou, Y., Hughes, C. E., & Fu, Y. (2021). Reinforced imitative graph representation learning for mobile user profiling: An adversarial training perspective. AAAI Conference on Artificial Intelligence (pp. 4410-4417). Vancouver, Canada.
  • Westerman, D., Spence, P. R., & Van Der Heide, B. (2014). Social media as information source: Recency of updates and credibility of information. Journal of computer-mediated communication, 19(2), 171-183.
  • Yaşa, E., & Bozyi̇ği̇t, S. (2012). Y kuşağı tüketicilerinin cep telefonu ve gsm operatörleri tercihi: mersin ilindeki üniversite öğrencilerinin tercihlerini belirlemeye yönelik pilot bir araştırma. Çağ Üniversitesi Sosyal Bilimler Dergisi, 9(1), 29-46.

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

Murat Fatih Tuna

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.

Keywords

February 6th Earthquake GSM providers Topic modelling YouTube users Consumer perceptions

References

  • AFAD. (2023a). Basın Bülteni-Kahramanmaraş’ta Meydana Gelen Depremler HK. ˗ 34. 15 Eylül 2023, https://www.afad.gov.tr/kahramanmarasta-meydana-gelen-depremler-hk-34.
  • AFAD. (2023b). 6 Şubat Deprem Bölgesindeki Aktivite Haritası. 15 Eylül 2023, https://twitter.com/DepremDairesi/status/1628044504061157377/photo/1.
  • 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.
  • Alghamdi, R., & Alfaqi, K. (2015). A survey of topic modeling in text mining. International Journal of Advanced Computer Science and Applications, 6(1), 147-153.
  • Almuqren, L., & Cristea, A. (2021). AraCust: A Saudi Telecom Tweets corpus for sentiment analysis. PeerJ Computer Science, 7, e510.
  • BTK. (2022). Türkiye Elektronik Haberleşme Sektörü Üç Aylık Pazar Verileri. 12 Eylül 2023, https://www.btk.gov.tr/uploads/pages/pazar-verileri/2022-q3.pdf
  • Chae, J., Thom, D., Bosch, H., Jang, Y., Maciejewski, R., Ebert, D. S., & Ertl, T. (2012). Spatiotemporal social media analytics for abnormal event detection and examination using seasonal-trend decomposition. 2012 IEEE conference on visual analytics science and technology (VAST). (pp. 143-152). Seatle, WA.
  • Corte, V. D., Iavazzi, A., & D’Andrea, C. (2015). Customer involvement through social media: The cases of some telecommunication firms. Journal of Open Innovation: Technology, Market, and Complexity, 1(1), 1-10.
  • Cui, W., Wu, Y., Liu, S., Wei, F., Zhou, M. X., & Qu, H. (2010). Context preserving dynamic word cloud visualization. 2010 IEEE Pacific Visualization Symposium (PacificVis) (pp. 121-128). Taipei, Taiwan.
  • Dasgupta, K., Singh, R., Viswanathan, B., Chakraborty, D., Mukherjea, S., Nanavati, A. A., & Joshi, A. (2008). Social ties and their relevance to churn in mobile telecom networks. Proceedings of the 11th international conference on Extending database technology: Advances in database technology. (pp. 668-677). Nantes, France.
  • Du, H. S., Ke, X., He, W., Chu, S. K. W., & Wagner, C. (2019). Achieving mobile social media popularity to enhance customer acquisition: Cases from P2P lending firms. Internet Research, 29(6), 1386-1409.
  • 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.
  • Evans, D. (2010). Social Media Marketing: The Next Generation of Business Engagement. John Wiley & Sons. Flores, B. E., & Clay Whybark, D. (1986). Multiple criteria ABC analysis. International Journal of Operations & Production Management, 6(3), 38-46.
  • Gürboğa, Ş., Gökçe, O., Mustafa, V., & Tüfekçi, K. (2016). Türkiye’de yüzey faylanması tehlikesinin değerlendirilmesi ve fay sakınım bantlarının oluşturulması. Doğal Kaynaklar ve Ekonomi Bülteni, 21, 29-45.
  • Güven Z. A., Diri B., & Çakaloğlu T. (2019). Comparison of topic modeling methods for type detection of turkish news. International Conference on Computer Science and Engineering (UBMK). (pp. 150-154). Samsun, Türkiye.
  • 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
  • Kızgın, Y. (2008). Genç Gsm abonelerinin operatör seçimlerini etkileyen değişkenlerin konumlandırılması üzerine bir alan araştırması: Muğla Üniversitesi öğrencileri örneği. Journal of Management and Economics Research, 6(10), 142 - 161,.
  • 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
  • Kostić, S. M., Simić, M. I., & Kostić, M. V. (2020). Social network analysis and churn prediction in telecommunications using graph theory. Entropy, 22(7), 1-23.
  • 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/
  • Li, J., Wang, J., Xu, N., Hu, Y., & Cui, C. (2018). Importance degree research of safety risk management processes of urban rail transit based on text mining method. Information, 9(2), 26.
  • 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.
  • O’Callaghan, D., Greene, D., Carthy, J., & Cunningham, P. (2015). An analysis of the coherence of descriptors in topic modeling. Expert Systems with Applications, 42(13), 5645-5657.
  • 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
  • Polatgil, M. (2023a). Analyzing comments made to the duolingo mobile application with topic modeling. International Journal of Computing and Digital Systems, 13(1), 223-230.
  • Polatgil, M. (2023b). TOGG otomobili için youtube yorumlarının konu modellemesi. International Marmara Social Sciences Congress (Imascon Spring). (pp.48-53). Kocaeli-Turkey.
  • Ran, Y. (2011). Considerations and suggestions on improvement of communication network disaster countermeasures after the wenchuan earthquake. IEEE Communications Magazine, 49(1), 44-47.
  • Ranjan, S., Sood, S., & Verma, V. (2018). twitter sentiment analysis of real-time customer experience feedback for predicting growth of indian telecom companies. 2018 4th International Conference on Computing Sciences (ICCS), 166-174.
  • Resch, B., Usländer, F., & Havas, C. (2018). Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment. Cartography and Geographic Information Science, 45(4), 362-376.
  • Ribeiro, H., Barbosa, B., Moreira, A. C., & Rodrigues, R. G. (2023). Determinants of churn in telecommunication services: A systematic literature review. Management Review Quarterly, 1-38.
  • Saldaña, M. (2022). Who is to blame? analysis of government and news media frames during the 2014 earthquake in Chile. Journalism Studies, 23(1), 25-47.
  • Şengün, H. İ., & Menteş, N. (2018). GSM Operatör markalarının tüketici açısından değerlendirilmesi. Mukaddime, 9(1), 209-228.
  • Shaw, R., Shiwaku Hirohide Kobayashi, K., & Kobayashi, M. (2004). Linking experience, education, perception and earthquake preparedness. Disaster Prevention and Management: An International Journal, 13(1), 39-49.
  • Smith, A., Hawes, T., & Myers, M. (2014). Hiearchie: visualization for hierarchical topic models. proceedings of the workshop on interactive language learning, Visualization, and Interfaces, 71-78.
  • STATISTA. (2022). Telecommunications Infrastructure & Equipment - Statistics & Facts. 12 Eylül 2023, https://www.statista.com/topics/2844/telecommunications-equipment/
  • STATISTA. (2023). Telecommunications Services - Statistics & Facts. 12 Eylül 2023, https://www.statista.com/topics/2665/telecommunications-services/
  • Sunny, E.-E., & Abolaji, O. S. (2016). Electronic customer relationship management (e-crm) & marketing performance: empirical evidence from nigeria telecom sector. Journal of Economics, Management and Trade, 11(1), 1-14.
  • Susanti, A. R., Djatna, T., & Kusuma, W. A. (2017). Twitter’s Sentiment Analysis on Gsm Services using Multinomial Naïve Bayes. TELKOMNIKA (Telecommunication Computing Electronics and Control), 15(3), 1354-1361.
  • Tetik N., & Albulut, İ. İ. (2023). 6 şubat 2023’te yaşanan depremin ekonomik ve finansal etkileri: ihracat üzerinden bir inceleme, İçinde M. Öztürk ve M. Kırca (Ed.), Kahramanmaraş merkezli depremler sonrası için akademik öneriler (ss. 93-103). 1000 Kitap.
  • Tundjungsari, V. (2013). Business intelligence with social media and data mining to support customer satisfaction in telecommunication industry. International Journal of Computer Science and Electronics Engineering (IJCSEE), 1(1), 61-64.
  • TÜRK TELEKOM. (2023). Deprem Bölgelerimizdeki Ücretsiz Mobil Araç ve WiFi Noktalarımız. 8 Eylül 2023, https://www.turktelekom.com.tr/tt-hakkimizda/duyurular/Sayfalar/deprem-bolgelerimizdeki-ucretsiz-wifi-noktalarimiz.aspx
  • TURKCELL. (2023). Afetle Mücadele. 8 Eylül 2023, https://www.turkcell.com.tr/tr/hakkimizda/kurumsal-iletisim/sosyal-sorumluluk/afetle-mucadele
  • Vakulenko, S., Müller, O., & vom Brocke, J. (2014). Enriching itunes app store categories via topic modeling. building a better world through information systems. The 5th International Conference on Information Systems (pp. 1-11). Auckland-New Zealand.
  • Vidya, N. A., Fanany, M. I., & Budi, I. (2015). Twitter sentiment to analyze net brand reputation of mobile phone providers. Procedia Computer Science, 72, 519-526.
  • VODAFONE. (2023). Afet Bilgilendirme. 8 Eylül 2023, https://www.vodafone.com.tr/afet-bilgilendirme.
  • Wang, D., Wang, P., Liu, K., Zhou, Y., Hughes, C. E., & Fu, Y. (2021). Reinforced imitative graph representation learning for mobile user profiling: An adversarial training perspective. AAAI Conference on Artificial Intelligence (pp. 4410-4417). Vancouver, Canada.
  • Westerman, D., Spence, P. R., & Van Der Heide, B. (2014). Social media as information source: Recency of updates and credibility of information. Journal of computer-mediated communication, 19(2), 171-183.
  • Yaşa, E., & Bozyi̇ği̇t, S. (2012). Y kuşağı tüketicilerinin cep telefonu ve gsm operatörleri tercihi: mersin ilindeki üniversite öğrencilerinin tercihlerini belirlemeye yönelik pilot bir araştırma. Çağ Üniversitesi Sosyal Bilimler Dergisi, 9(1), 29-46.
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
 Download Cover Image