Araştırma Makalesi
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Sosyal Bilimlerde Veri Madenciliğinin Pazarlama Alanında Kullanımı

Yıl 2022, Cilt: 22 Sayı: Özel Sayı 2, 197 - 212, 31.12.2022
https://doi.org/10.18037/ausbd.1227342

Öz

Geçmişi ve bugünü anlamanın, geleceğe daha net bakmamıza yardım ettiği söylenebilir. Özellikle bilgi çağında, dijitalleşmenin de katkısıyla oluşan devasa veriler bu anlamlandırmayı daha önemli kılmaktadır. Bunu başarabilmek için elimizdeki en etkili yöntemlerden biri ise veri madenciliğidir. Veri madenciliği söz konusu verilerin içerisinde anlamlı ilişkileri, kalıpları ve eğilimleri keşfetmeye dayalı üretkenliği arttırmaya yönelik bir araçtır. Sosyal bilimlerde ve pazarlama alanında sıklıkla kullanılan veri madenciliği, keşfettiği anlamlı kalıplar ve ilişkilerle, müşterilerin gelecekteki davranışlarını tahmin etmeye yönelik öngörü geliştirmekte; ürün tekliflerinin nasıl yapılandırılması gerektiği gibi satış ve hizmet fonksiyonlarını destekleyerek işletmeler için birçok avantaj yaratmaktadır. Bu bağlamda çalışmada, sosyal bilimlerde veri madenciliği ve uygulamalarına ilişkin genel bilgi verilmesi, ardından pazarlama alanında veri madenciliği kullanımının değerlendirilmesi amaçlanmıştır. Bu sayede veri madenciliği kavramının sosyal bilimciler açısından daha net anlaşılmasına ve benimsenmesine, pazarlama alanında veri madenciliği uygulamalarının artmasına, dolayısıyla teoriye ve sektöre sağlayacağı katkıyı arttırmasına destek olacağı düşünülmektedir.

Kaynakça

  • Agarwal, S. (2013). Data mining: Data mining concepts and techniques [Full Paper]. International Conference on Machine Intelligence and Research Advancement, Katra, JK, India. Erişim adresi: https://ieeexplore.ieee.org/stamp/stamp.jsparnumber=6918822&casa_token=6disTaBAQAsAAAAA:ByVESK6tGqccbwC9FcHZZue6z5QiTnqmqzYDVOk0svwXbnioW1a0a8B9utGjMYBNM4iTA4VXF8s&tag=1
  • Akbıyık, A. (2019). Sosyal bilimlerde metin madenciliği wordstat uygulamaları. Sakarya: Sakarya Yayıncılık.
  • Akpınar, H. (2000). Veri tabanlarında bilgi keşfi ve veri madenciliği. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 29(1), 1-22. Erişim adresi: https://scholar.google.com.tr/scholar?hl=tr&as_sdt=0,5&cluster=7334736236434332959
  • Albayrak, M., Topal, K. ve Altıntaş, V. (2017). Sosyal medya üzerinde veri analizi: Twitter. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22 (Kayfor 15 Özel Sayısı), 1991-1998. Erişim adresi: https://dergipark.org.tr/en/download/article-file/1026277
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  • Berkhin, P. (2006). A survey of clustering data mining techniques. Kogan, J., Nicholas, C., Teboulle, M. (Ed.), Grouping multidimensional data (pp. 25-71) in. Heidelberg Springer Press.
  • Berry, M. J. ve Linoff, G. S. (2004). Data mining techniques: for marketing, sales, and customer relationship management. New York: John Wiley & Sons.
  • Cemaloğlu, N. ve Duykuluoğlu, A. (2020). Sosyal bilimlerde veri madenciliği. Ankara: Pegem Akademi.
  • Chen, I. J. ve Popovich, K. (2003). Understanding customer relationship management (CRM): People, process and technology. Business Process Management Journal, 9(5), 672-688. doi: 10.1108/14637150310496758.
  • Chrzanowski, M. ve Levick, D. (2012). Using Twitter to Predict Voting Behavior. Erişim adresi:http://cs229.stanford.edu/proj2012/ChrzanowskiLevick-UsingTwitterToPredictVotingBehavior.pdf
  • Chye, K. H. ve Gerry, C. K. L. (2002). Data mining and customer relationship marketing in the banking industry. Singapore Management Review, 24(2), 1-28. Erişim adresi: https://go.gale.com/ps/i.do?id=GALE%7CA87703083&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=01295977&p=AONE&sw=w&userGroupName=anon%7E4b49aa63
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  • Durdu, M. (2012). Application of data mining in customer relationship management market basket analysis in a retailer store (Doktora Tezi). İzmir Dokuz Eylül Üniversitesi, İzmir.
  • Dyche, J. ve O'Brien, M. M. (2002). The CRM handbook: a business guide to customer relationship management. Boston: Addison-Wesley.
  • Džeroski, S. (2009). Relational data mining. Maiomon, O., Rokach, L. (Ed.), Data mining and knowledge discovery handbook (pp. 887-911) in. Boston: Springer.
  • Enke, D. ve Thawornwong, S. (2005). The use of data mining and neural networks for forecasting stock market returns. Expert Systems With Applications, 29(4), 927-940. doi: 10.1016/j.eswa.2005.06.024
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  • Haenlein, M. ve Kaplan, A. (2019). A brief history of artificial intelligence: on the past, present, and future of artificial intelligence. California Management Review, 61(4), 5-14. doi: 10.1177/000812561986492
  • Han, J., Pei, J. ve Tong, H. (2022). Data mining: concepts and techniques. USA: Morgan Kaufmann.
  • Hastie, T., Tibshirani, R., Friedman, J. H. ve Friedman, J. H. (2009). The elements of statistical learning: data mining, inference, and prediction. New York: Springer.
  • Haşıloğlu, S. B. (2022). Pazarlama araştırması ve analitiği, Ankara: Nobel Bilimsel Eserler
  • Hossain, M. Z., Akhtar, M. N., Ahmad, R. B. ve Rahman, M. (2019). A dynamic k-means clustering for data mining. Indonesian Journal of Electrical engineering and computer science, 13(2), 521-526. doi: 10.11591/ijeecs.v13.i2.pp521-526
  • Howard, J. (2019). Artificial intelligence: implications for the future of work. American Journal of Industrial Medicine, 62(11), 917–926. doi: 10.1002/ajim.23037
  • Jackson, J. (2002). Data mining; a conceptual overview. Communications of the Association for Information Systems, 8(1), 267-296. doi: 10.17705/1CAIS.00819
  • Kashwan, K. R. ve Velu, C. M. (2013). Customer segmentation using clustering and data mining techniques. International Journal of Computer Theory and Engineering, 5(6), 856-861. doi: 10.7763/IJCTE.2013.V5.811
  • Kaunang, F. J. ve Rotikan, R. (2018). Students' academic performance prediction using data mining [Full Paper]. Third International Conference on Informatics and Computing, Palembang, Indonesia. Erişim adresi: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8780547
  • Kaur, P., Singh, M. ve Josan, G. S. (2015). Classification and prediction based data mining algorithms to predict slow learners in education sector. Procedia Computer Science, 57, 500-508. doi: 10.1016/j.procs.2015.07.372
  • Koyuncugil, A. S. (2007). Veri madenciliği ve sermaye piyasalarına uygulaması. Sermaye Piyasası Kurulu Araştırma Raporu, 28 Şubat 2007, Ankara. Erişim adresi: http://koyuncugil.org/en/dosyalar/933.pdf
  • Köktürk, M. S. ve Dirsehan, T. (2012). Veri madenciliği ile pazarlama etkileşimi. Ankara: Nobel Yayıncılık.
  • Kuonen, D. (2004). Data mining and statistics: what is the connection?. The Data Administration Newsletter, 30, 1-6. Erişim adresi: https://www.researchgate.net/profile/Diego-Kuonen-2/publication/228757258_Data_Mining_and_Statistics_What_is_the_Connection/links/59bb6ec60f7e9b48a289dc96/Data-Mining-and-Statistics-What-is-the-Connection.pdf
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Yıl 2022, Cilt: 22 Sayı: Özel Sayı 2, 197 - 212, 31.12.2022
https://doi.org/10.18037/ausbd.1227342

Öz

Kaynakça

  • Agarwal, S. (2013). Data mining: Data mining concepts and techniques [Full Paper]. International Conference on Machine Intelligence and Research Advancement, Katra, JK, India. Erişim adresi: https://ieeexplore.ieee.org/stamp/stamp.jsparnumber=6918822&casa_token=6disTaBAQAsAAAAA:ByVESK6tGqccbwC9FcHZZue6z5QiTnqmqzYDVOk0svwXbnioW1a0a8B9utGjMYBNM4iTA4VXF8s&tag=1
  • Akbıyık, A. (2019). Sosyal bilimlerde metin madenciliği wordstat uygulamaları. Sakarya: Sakarya Yayıncılık.
  • Akpınar, H. (2000). Veri tabanlarında bilgi keşfi ve veri madenciliği. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 29(1), 1-22. Erişim adresi: https://scholar.google.com.tr/scholar?hl=tr&as_sdt=0,5&cluster=7334736236434332959
  • Albayrak, M., Topal, K. ve Altıntaş, V. (2017). Sosyal medya üzerinde veri analizi: Twitter. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22 (Kayfor 15 Özel Sayısı), 1991-1998. Erişim adresi: https://dergipark.org.tr/en/download/article-file/1026277
  • Batool, I. ve Khan, T. A. (2022). Software fault prediction using data mining, machine learning and deep learning techniques: A systematic literature review. Computers and Electrical Engineering, 100, 107886. doi: 10.1016/j.compeleceng.2022.107886
  • Berg, J. E. ve Rietz, T. A. (2003). Prediction markets as decision support systems. Information Systems Frontiers, 5(1), 79-93. Erişim adresi: https://link.springer.com/content/pdf/10.1023/A:1022002107255.pdf
  • Berkhin, P. (2006). A survey of clustering data mining techniques. Kogan, J., Nicholas, C., Teboulle, M. (Ed.), Grouping multidimensional data (pp. 25-71) in. Heidelberg Springer Press.
  • Berry, M. J. ve Linoff, G. S. (2004). Data mining techniques: for marketing, sales, and customer relationship management. New York: John Wiley & Sons.
  • Cemaloğlu, N. ve Duykuluoğlu, A. (2020). Sosyal bilimlerde veri madenciliği. Ankara: Pegem Akademi.
  • Chen, I. J. ve Popovich, K. (2003). Understanding customer relationship management (CRM): People, process and technology. Business Process Management Journal, 9(5), 672-688. doi: 10.1108/14637150310496758.
  • Chrzanowski, M. ve Levick, D. (2012). Using Twitter to Predict Voting Behavior. Erişim adresi:http://cs229.stanford.edu/proj2012/ChrzanowskiLevick-UsingTwitterToPredictVotingBehavior.pdf
  • Chye, K. H. ve Gerry, C. K. L. (2002). Data mining and customer relationship marketing in the banking industry. Singapore Management Review, 24(2), 1-28. Erişim adresi: https://go.gale.com/ps/i.do?id=GALE%7CA87703083&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=01295977&p=AONE&sw=w&userGroupName=anon%7E4b49aa63
  • Davenport, T. H., Harris, J. G. ve Kohli, A. K. (2001). How do they know their customers so well?, MIT Sloan Management Review, 42(2), 63-73. Erişim adresi: https://www.proquest.com/openview/582eb1412266675fd7358a0f3c240d4d/1?pq-origsite=gscholar&cbl=26142
  • Drozdenko, R. G. ve Drake, P. D. (2002). Optimal database marketing: strategy, development, and data mining. London: Sage Publicaitons Ltd.
  • Durdu, M. (2012). Application of data mining in customer relationship management market basket analysis in a retailer store (Doktora Tezi). İzmir Dokuz Eylül Üniversitesi, İzmir.
  • Dyche, J. ve O'Brien, M. M. (2002). The CRM handbook: a business guide to customer relationship management. Boston: Addison-Wesley.
  • Džeroski, S. (2009). Relational data mining. Maiomon, O., Rokach, L. (Ed.), Data mining and knowledge discovery handbook (pp. 887-911) in. Boston: Springer.
  • Enke, D. ve Thawornwong, S. (2005). The use of data mining and neural networks for forecasting stock market returns. Expert Systems With Applications, 29(4), 927-940. doi: 10.1016/j.eswa.2005.06.024
  • Fayyad, U., Piatetsky-Shapiro, G. ve Smyth, P. (1996). From data mining to knowledge discovery in databases. AI Magazine, 17(3), 37-37. doi: 10.1609/aimag.v17i3.1230
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics (4rd Edition). London: Sage Publicaitons Ltd.
  • Foss, B. ve Stone, M. (2001). Successful customer relationship marketing: new thinking, new strategies, new tools for getting closer to your customers. Kogan: Page Publishers.
  • Ganesh, S. (2002). Data mining: should it be included in the statistics curriculum? [Full Paper]. 6th İnternational Conference on Teaching Statistics, Cape Town, South Africa. Erişim adresi: https://www.stat.auckland.ac.nz/~iase/publications/1/3l4_gane.pdf
  • Gartner Group (2022). Data mining, Erişim adresi: https://www.gartner.com/en/information-technology/glossary/data-mining
  • Gupta, B., Rawat, A., Jain, A., Arora, A. ve Dhami, N. (2017). Analysis of various decision tree algorithms for classification in data mining. International Journal of Computer Applications, 163(8), 15-19. Erişim adresi:https://www.academia.edu/52959875/Analysis_of_Various_Decision_Tree_Algorithms_for_Classification_in_Data_Mining?from=cover_page
  • Haenlein, M. ve Kaplan, A. (2019). A brief history of artificial intelligence: on the past, present, and future of artificial intelligence. California Management Review, 61(4), 5-14. doi: 10.1177/000812561986492
  • Han, J., Pei, J. ve Tong, H. (2022). Data mining: concepts and techniques. USA: Morgan Kaufmann.
  • Hastie, T., Tibshirani, R., Friedman, J. H. ve Friedman, J. H. (2009). The elements of statistical learning: data mining, inference, and prediction. New York: Springer.
  • Haşıloğlu, S. B. (2022). Pazarlama araştırması ve analitiği, Ankara: Nobel Bilimsel Eserler
  • Hossain, M. Z., Akhtar, M. N., Ahmad, R. B. ve Rahman, M. (2019). A dynamic k-means clustering for data mining. Indonesian Journal of Electrical engineering and computer science, 13(2), 521-526. doi: 10.11591/ijeecs.v13.i2.pp521-526
  • Howard, J. (2019). Artificial intelligence: implications for the future of work. American Journal of Industrial Medicine, 62(11), 917–926. doi: 10.1002/ajim.23037
  • Jackson, J. (2002). Data mining; a conceptual overview. Communications of the Association for Information Systems, 8(1), 267-296. doi: 10.17705/1CAIS.00819
  • Kashwan, K. R. ve Velu, C. M. (2013). Customer segmentation using clustering and data mining techniques. International Journal of Computer Theory and Engineering, 5(6), 856-861. doi: 10.7763/IJCTE.2013.V5.811
  • Kaunang, F. J. ve Rotikan, R. (2018). Students' academic performance prediction using data mining [Full Paper]. Third International Conference on Informatics and Computing, Palembang, Indonesia. Erişim adresi: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8780547
  • Kaur, P., Singh, M. ve Josan, G. S. (2015). Classification and prediction based data mining algorithms to predict slow learners in education sector. Procedia Computer Science, 57, 500-508. doi: 10.1016/j.procs.2015.07.372
  • Koyuncugil, A. S. (2007). Veri madenciliği ve sermaye piyasalarına uygulaması. Sermaye Piyasası Kurulu Araştırma Raporu, 28 Şubat 2007, Ankara. Erişim adresi: http://koyuncugil.org/en/dosyalar/933.pdf
  • Köktürk, M. S. ve Dirsehan, T. (2012). Veri madenciliği ile pazarlama etkileşimi. Ankara: Nobel Yayıncılık.
  • Kuonen, D. (2004). Data mining and statistics: what is the connection?. The Data Administration Newsletter, 30, 1-6. Erişim adresi: https://www.researchgate.net/profile/Diego-Kuonen-2/publication/228757258_Data_Mining_and_Statistics_What_is_the_Connection/links/59bb6ec60f7e9b48a289dc96/Data-Mining-and-Statistics-What-is-the-Connection.pdf
  • Larose, D. T. ve Larose, C. D. (2014). Discovering knowledge in data: an introduction to data mining. New York: John Wiley & Sons.
  • Liu, S., Duffy, A. H., Whitfield, R. I., ve Boyle, I. M. (2010). Integration of decision support systems to improve decision support performance. Knowledge and Information Systems, 22(3), 261-286. doi: 10.1007/s10115-009-0192-4
  • Markov, Z. ve Larose, D. T. (2007). Data mining the web: uncovering patterns in web content, structure, and usage. New York: John Wiley & Sons.
  • Nasira, G. M. ve Hemageetha, N. (2012). Vegetable price prediction using data mining classification technique [Full Paper]. International Conference on Pattern Recognition, Informatics and Medical Engineering, Salem, India. Erişim adresi: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6208294
  • Piatetsky-Shapiro, G. (2007). Data mining and knowledge discovery 1996 to 2005: overcoming the hype and moving from “university” to “business” and “analytics”. Data Mining and Knowledge Discovery, 15(1), 99-105. doi: 10.1007/s10618-006-0058-2
  • Queiroz-Sousa, P. O. ve Salgado, A. C. (2019). A review on OLAP technologies applied to information networks. ACM Transactions on Knowledge Discovery from Data, 14(1), 1-25. doi: 10.1145/3370912
  • Rud, O. P. (2001). Data mining cookbook: modeling data for marketing, risk, and customer relationship management. New York: John Wiley & Sons.
  • Sadath, L. (2013). Data mining in e-commerce: a CRM platform. International Journal of Computer Applications, 68(24), 32-37. doi: 10.5120/11729-7383
  • Savaş, S., Topaloğlu, N. ve Yılmaz, M. (2012). Veri madenciliği ve Türkiye’deki uygulama örnekleri. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, 11(21), 1-23. Erişim adresi: https://dergipark.org.tr/en/download/article-file/199592
  • Shaikh, A. A., ve Karjaluoto, H. (2015). Making the most of information technology & systems usage: a literature review, framework and future research agenda. Computers in Human Behavior, 49, 541-566. doi: 10.1016/j.chb.2015.03.059
  • Sharma, H. ve Kumar, S. (2016). A survey on decision tree algorithms of classification in data mining. International Journal of Science and Research, 5(4), 2094-2097. Erişim adresi: https://www.researchgate.net/profile/SunilKumar310/publication/324941161_A_Survey_on_Decision_Tree_Algorithms_of_Classification_in_Data_Mining/links/5aebdfe6a6fdcc8508b6e8bb/A-Survey-on-Decision-Tree-Algorithms-of-Classification-in-Data-Mining.pdf
  • Shaw, M. J., Subramaniam, C., Tan, G. W. ve Welge, M. E. (2001). Knowledge management and data mining for marketing. Decision support systems, 31(1), 127-137. doi: 10.1016/S0167-9236(00)00123-8
  • Taşçı, M. T. ve Dal, N. E. (2022). Algoritmik pazarlama. Baş, M., Tarakçı, İ.E., Aslan, R. (Ed.), Dijitalleşme (pp. 317-357) in. İstanbul: Efeakademi Yayınları.
  • Thuraisingham, B. (2003). Web data mining and applications in business intelligence and counter-terrorism. USA: CRC Press.
  • Türk, B. (2022). Could huggy wuggy's popularity be deeper than it may seem like on the surface? [Abstract]. 2nd Conference on Social Sciences, Humanities and Education, İstanbul, Turkey. Erişim adresi: https://usbed.org/wp-content/uploads/2022/12/Conference-Book-Web-55MB.pdf
  • Tüzüntürk, S. (2010). Veri madenciliği ve istatistik. Uludağ Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 29(1), 65-90. Erişim adresi: http://www.uludag.edu.tr/dosyalar/iibfdergi/genel-dokuman/2010_1/ASL04.pdf
  • Vanneschi, L., Horn, D. M., Castelli, M. vePopovič, A. (2018). An artificial intelligence system for predicting customer default in e-commerce. Expert Systems with Applications, 104, 1-21. doi: 10.1016/j.eswa.2018.03.025
  • Velu, C. M. ve Kashwan, K. R. (2012). Performance analysis for visual data mining classification techniques of decision tree, ensemble and SOM. International Journal of Computer Applications, 57(22), 65-71. doi: 10.5120/9426-3874
  • Vijiyarani, S. ve Sudha, S. (2013). Disease prediction in data mining technique-a survey. International Journal of Computer Applications and Information Technology, 2(1), 17-21. Erişim adresi: https://www.ijcait.com/IJCAIT/21/213.pdf
Toplam 56 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Bahar Türk Bu kişi benim

Yayımlanma Tarihi 31 Aralık 2022
Gönderilme Tarihi 15 Ekim 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 22 Sayı: Özel Sayı 2

Kaynak Göster

APA Türk, B. (2022). Sosyal Bilimlerde Veri Madenciliğinin Pazarlama Alanında Kullanımı. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 22(Özel Sayı 2), 197-212. https://doi.org/10.18037/ausbd.1227342