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Data Analysis of the Authenticity of the National Anthems and Turkish National Anthem

Year 2023, Volume: 10 Issue: 1-Prof. Dr. Feyzullah EROĞLU Armağan Sayısı, 96 - 109, 30.05.2023
https://doi.org/10.47097/piar.1180263

Abstract

National anthems are one of the indicators of independence of countries and talk about the sense of independence of countries. In this study, the National Anthem of the Republic of Turkey, Turkish National Anthem, is analyzed by data mining techniques. While analyzing Turkish National Anthem, the anthems of the member states of the Turkic Council with which they have a common language tie, the anthems of the member states of the Organization of Islamic Cooperation, which are thought to have common religious values, and the anthems of the European Union Member States, since Turkey is a European country, were included in the analysis. The analysis includes cluster analysis and association analysis techniques in terms of data mining. In terms of text mining, the similarities of Turkish National Anthem and other national anthems were examined in terms of word size, title size and sentiment analysis. As a result of the analysis, all the country anthems that were compared in one cluster, whose data were calculated as two clusters by cluster analysis, were included, while Turkish National Anthem took place alone in the other cluster. This is an important indicator in revealing the originality of Turkish National Anthem. Again, the analyzes in 3 dimensions under the title of text mining did not reveal a similarity between Turkish National Anthem and the national anthems compared. The results of the association analysis are important in terms of showing the use of common words and words in national anthems together.

References

  • Abril, C. R. (2016). A national anthem: Patriotic Symbol or Democratic Action? In Patriotism and Nationalism in Music Education (pp. 77-94). Routledge.
  • Agrawal, R., Imieliński, T., & Swami, A. (1993, June). Mining Association Rules Between Sets of Items in Large Databases. In Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data (pp. 207-216).
  • Akarsu, S. İstiklal Marşı ve İcrasına Yönelik Bir Analiz Çalışması. Turkish Studies, 16(5), 1-35.
  • Aktaş, H. E. (2014). Milli Marşların Siyaset Biliminin Bazı Kavramları Açısından Değerlendirilmesi. Gazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 15(2), 71-92.
  • Al-Maolegi, M., & Arkok, B. (2014). An Improved Apriori Algorithm for Association Rules. arXiv preprint arXiv:1403.3948.
  • AL-Zawaidah, F. H., Jbara, Y. H., & Marwan, A. L. (2011). An Improved Algorithm for Mining Association Rules in Large Databases. World of Computer Science and Information Technology Journal, 1(7), 311-316.
  • Arslan, M. F., Mehmood, M. A., & Haroon, H. (2021). Stylistic and Textual Analysis of Pakistani National Anthem. Journal of Social Sciences and Humanities, 1(2), 21-29.
  • Balbi, S., Misuraca, M., & Scepi, G. (2018). Combining Different Evaluation Systems on Social Media for Measuring User Satisfaction. Information Processing & Management, 54(4), 674-685.
  • Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research, 3(Jan), 993-1022.
  • Csepeli, G., & Örkény, A. (1998). The Imagery of National Anthems in Europe. Nation, Ethnicity, Minority And Border. Contributions to an International Sociology, 37-56.
  • Dlodlo, S. (2019). An Investigation into Nation Building through the National Anthem in Zimbabwe: a Sociolinguistic Approach (Doctoral dissertation).
  • Essam, B. A. (2015). Melopoetics of the Contemporary “National Anthem” of Egypt and its Translations: A case Study. Higher Education of Social Science, 8(1), 1-11.
  • Gilboa, A., & Bodner, E. (2009). What are Your Thoughts when the National Anthem is Playing? An Empirical Exploration. Psychology of Music, 37(4), 459-484.
  • Han, J., & Kamber, M. (2006). Data Mining: Concepts and Techniques, 2nd. University of Illinois at Urbana Champaign: Morgan Kaufmann.
  • Haşıloğlu, M., & Budak, İ. (2019). Sanal mağaza Drone Depo Yer ve Önceliklerinin Tespitine Yönelik Bir Araştırma Süreci Modeli. Journal of Internet Applications and Management, 10(2), 63-79.
  • Krestel, R., Fankhauser, P., & Nejdl, W. (2009, October). Latent Dirichlet Allocation for Tag Recommendation. In Proceedings of the Third ACM Conference on Recommender Systems (pp. 61-68).
  • Lauenstein, O., Murer, J. S., Boos, M., & Reicher, S. (2015). ‘Oh motherland I pledge to thee…’: a Study into Nationalism, Gender and The Representation of an Imagined Family Within National Anthems. Nations and Nationalism, 21(2), 309-329.
  • Liu, B. (2012). Sentiment Analysis and Opinion Mining. Synthesis Lectures on Human Language Technologies, 5(1), 1-167.
  • Pelleg, D., & Moore, A. W. (2000, June). X-means: Extending k-means with Efficient Estimation of the Number of Clusters. In Icml (Vol. 1, pp. 727-734).
  • Sabah, L., & Bayraktar, H. (2020). Veri Madenciliği Birliktelik Kuralları ile Binaların Risk Durumlarının Analizi: Kaynaşlı, Düzce Örneği. Gazi Mühendislik Bilimleri Dergisi, 6(1), 70-78.
  • Souza, A. A. D. (2008). Do the rigth, be firm, be fair..: a Systemic Funcional İnvestigation of National Anthems Written in English.
  • Van Gınderachter, M. (2020). Encounters Wıth the Belgıan Flag and the National Anthem. In the Everyday Nationalism of Workers (pp. 105-124). Stanford University Press.
  • Wang, X., & Grimson, E. (2007). Spatial Latent Dirichlet Allocation. Advances in Neural İnformation Processing Systems, 20.
  • Wilson, T., Wiebe, J., & Hoffmann, P. (2005, October). Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis. In Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (pp. 347-354).
  • Wu, X., Kumar, V., Ross Quinlan, J., Ghosh, J., Yang, Q., Motoda, H., ... & Steinberg, D. (2008). Top 10 Algorithms in Data Mining. Knowledge and Information Systems, 14(1), 1-37.
  • Xu, R. Ve Wunsch, D. (2008). Clustering (Vol. 10). John Wiley & Sons.

Ülke Milli Marşları ve İstiklal Marşı’nın Özgünlüğünün Veri Analizi

Year 2023, Volume: 10 Issue: 1-Prof. Dr. Feyzullah EROĞLU Armağan Sayısı, 96 - 109, 30.05.2023
https://doi.org/10.47097/piar.1180263

Abstract

Milli marşlar ülkelerin bağımsızlık göstergelerinden biridir ve ülkelerin bağımsızlık duygusundan bahseder. Bu çalışmada Türkiye Cumhuriyeti milli marşı İstiklal Marşı’nın veri analizi yapılmıştır. İstiklal Marşı analiz edilirken ortak dil bağının bulunduğu Türk Keneşi üye ülke marşları, ortak dini değerleri bulunduğu düşünülen İslam İş Birliği Teşkilatı üye ülke marşları ve Türkiye’nin bir Avrupa ülkesi olmasından ötürü Avrupa Birliği Üye ülkelerinin marşları analize dahil edilmiştir. Analiz veri madenciliği açısından kümeleme analizi ve birliktelik analizini tekniklerini içermektedir. Metin madenciliği açısından ise kelime boyutunda, başlık boyutunda ve duygu analizi boyutunda İstiklal Marşı ve diğer milli marşların benzerlikleri incelenmiştir. Analiz sonucunda kümeleme analizi ile veriler iki küme olarak hesaplanmış bir kümede karşılaştırılan tüm ülke marşları yer alırken İstiklal Marşı diğer kümede tek başına yer almıştır. Bu İstiklal Marşının özgünlüğünü ortaya koymada önemli bir göstergedir. Yine metin madenciliği başlığı altındaki 3 boyuttaki analizler İstiklal Marşı ile karşılaştırılan milli marşlar arasında bir benzerlik ortaya koyamamıştır. Birliktelik analizi sonuçları ise milli marşlardaki ortak kelimelerin ve kelimelerin birlikte kullanımını göstermesi açısından önemlidir.

References

  • Abril, C. R. (2016). A national anthem: Patriotic Symbol or Democratic Action? In Patriotism and Nationalism in Music Education (pp. 77-94). Routledge.
  • Agrawal, R., Imieliński, T., & Swami, A. (1993, June). Mining Association Rules Between Sets of Items in Large Databases. In Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data (pp. 207-216).
  • Akarsu, S. İstiklal Marşı ve İcrasına Yönelik Bir Analiz Çalışması. Turkish Studies, 16(5), 1-35.
  • Aktaş, H. E. (2014). Milli Marşların Siyaset Biliminin Bazı Kavramları Açısından Değerlendirilmesi. Gazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 15(2), 71-92.
  • Al-Maolegi, M., & Arkok, B. (2014). An Improved Apriori Algorithm for Association Rules. arXiv preprint arXiv:1403.3948.
  • AL-Zawaidah, F. H., Jbara, Y. H., & Marwan, A. L. (2011). An Improved Algorithm for Mining Association Rules in Large Databases. World of Computer Science and Information Technology Journal, 1(7), 311-316.
  • Arslan, M. F., Mehmood, M. A., & Haroon, H. (2021). Stylistic and Textual Analysis of Pakistani National Anthem. Journal of Social Sciences and Humanities, 1(2), 21-29.
  • Balbi, S., Misuraca, M., & Scepi, G. (2018). Combining Different Evaluation Systems on Social Media for Measuring User Satisfaction. Information Processing & Management, 54(4), 674-685.
  • Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research, 3(Jan), 993-1022.
  • Csepeli, G., & Örkény, A. (1998). The Imagery of National Anthems in Europe. Nation, Ethnicity, Minority And Border. Contributions to an International Sociology, 37-56.
  • Dlodlo, S. (2019). An Investigation into Nation Building through the National Anthem in Zimbabwe: a Sociolinguistic Approach (Doctoral dissertation).
  • Essam, B. A. (2015). Melopoetics of the Contemporary “National Anthem” of Egypt and its Translations: A case Study. Higher Education of Social Science, 8(1), 1-11.
  • Gilboa, A., & Bodner, E. (2009). What are Your Thoughts when the National Anthem is Playing? An Empirical Exploration. Psychology of Music, 37(4), 459-484.
  • Han, J., & Kamber, M. (2006). Data Mining: Concepts and Techniques, 2nd. University of Illinois at Urbana Champaign: Morgan Kaufmann.
  • Haşıloğlu, M., & Budak, İ. (2019). Sanal mağaza Drone Depo Yer ve Önceliklerinin Tespitine Yönelik Bir Araştırma Süreci Modeli. Journal of Internet Applications and Management, 10(2), 63-79.
  • Krestel, R., Fankhauser, P., & Nejdl, W. (2009, October). Latent Dirichlet Allocation for Tag Recommendation. In Proceedings of the Third ACM Conference on Recommender Systems (pp. 61-68).
  • Lauenstein, O., Murer, J. S., Boos, M., & Reicher, S. (2015). ‘Oh motherland I pledge to thee…’: a Study into Nationalism, Gender and The Representation of an Imagined Family Within National Anthems. Nations and Nationalism, 21(2), 309-329.
  • Liu, B. (2012). Sentiment Analysis and Opinion Mining. Synthesis Lectures on Human Language Technologies, 5(1), 1-167.
  • Pelleg, D., & Moore, A. W. (2000, June). X-means: Extending k-means with Efficient Estimation of the Number of Clusters. In Icml (Vol. 1, pp. 727-734).
  • Sabah, L., & Bayraktar, H. (2020). Veri Madenciliği Birliktelik Kuralları ile Binaların Risk Durumlarının Analizi: Kaynaşlı, Düzce Örneği. Gazi Mühendislik Bilimleri Dergisi, 6(1), 70-78.
  • Souza, A. A. D. (2008). Do the rigth, be firm, be fair..: a Systemic Funcional İnvestigation of National Anthems Written in English.
  • Van Gınderachter, M. (2020). Encounters Wıth the Belgıan Flag and the National Anthem. In the Everyday Nationalism of Workers (pp. 105-124). Stanford University Press.
  • Wang, X., & Grimson, E. (2007). Spatial Latent Dirichlet Allocation. Advances in Neural İnformation Processing Systems, 20.
  • Wilson, T., Wiebe, J., & Hoffmann, P. (2005, October). Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis. In Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (pp. 347-354).
  • Wu, X., Kumar, V., Ross Quinlan, J., Ghosh, J., Yang, Q., Motoda, H., ... & Steinberg, D. (2008). Top 10 Algorithms in Data Mining. Knowledge and Information Systems, 14(1), 1-37.
  • Xu, R. Ve Wunsch, D. (2008). Clustering (Vol. 10). John Wiley & Sons.
There are 26 citations in total.

Details

Primary Language Turkish
Journal Section Research Articles
Authors

Günay Kılıç 0000-0003-2236-7535

İbrahim Budak 0000-0001-7762-6114

Selçuk Burak Haşıloğlu 0000-0003-4512-6531

Publication Date May 30, 2023
Published in Issue Year 2023 Volume: 10 Issue: 1-Prof. Dr. Feyzullah EROĞLU Armağan Sayısı

Cite

APA Kılıç, G., Budak, İ., & Haşıloğlu, S. B. (2023). Ülke Milli Marşları ve İstiklal Marşı’nın Özgünlüğünün Veri Analizi. Pamukkale Üniversitesi İşletme Araştırmaları Dergisi, 10(1-Prof. Dr. Feyzullah EROĞLU Armağan Sayısı), 96-109. https://doi.org/10.47097/piar.1180263

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