Araştırma Makalesi
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Yapay Zeka, Makine Öğrenmesi ve Reklamcılık Konulu Araştırmaların Bibliyometrik Analizi

Yıl 2024, Sayı: 12, 114 - 147, 27.06.2024
https://doi.org/10.56676/kiad.1349868

Öz

Yapay zeka ve makine öğrenmesi, modern dünyadaki karmaşıklığı ve hızla değişen ihtiyaçları karşılamada önemli bir role sahip olup iletişim süreçlerini etkili hale getirmektedir. Reklamcılık sektöründe yapay zeka ve makine öğrenmesinin kullanımı, daha verimli, kişiselleştirilmiş ve uygun maliyetli reklamcılık süreçlerini optimize etme potansiyeline sahiptir. Bu çalışmada, yapay zeka ve makine öğrenmesi ile reklamcılık alanlarının birleştiği ve bu kavramların konu edildiği, Web of Science (WOS) platformundaki bilimsel araştırmaların bibliyometrik özellikleri incelenmiştir. Araştırmanın amacı, yapay zeka, makine öğrenmesi ve reklamcılık alanlarındaki araştırmacılara ve akademisyenlere yol gösterici bir başlangıç kaynağı oluşturmaktır. Araştırma, en üretken dergiler, yazarlar, ülkeler ve kurumlar gibi verileri ortaya koymakta ve alanın gelişimine yönelik bir çerçeve sunmaktadır. Sonuçlara göre; yapay zeka ve makine öğrenmesinin reklamcılık alanında giderek artan bir etkiye sahip olduğunu ve bu alanların disiplinler arası iş birlikleriyle zenginleştiğini, ayrıca literatürde çevrimiçi reklamcılık, sosyal medya, büyük veri gibi konulara yönelik belirgin bir eğilim olduğu görülmektedir.

Kaynakça

  • Arango Espinal, E., Ceballos Molano, R. ve Osorio Andrade, C. F. (2021). Investigación en publicidad política: Un análisis bibliométrico. Revista Guillermo de Ockham, 18(2), 181-189. https://doi.org/10.21500/22563202.4574
  • Arf, C. (1959). Makine düşünebilir mi ve nasıl düşünebilir? Atatürk Üniversitesi 1958-1959 Öğretim Yılı Halk Konferansları(1), 91-103. Batu, M. ve Yapıcıoğlu Ayaz, Y. (2021). A comparative bibliometric analysis on graduate theses in the field of public relations and advertising in Turkey. International Journal of Management Economics and Business, 17(2). https://doi.org/10.17130/ijmeb.785223
  • Becan, C. (2019). Reklamcılık literatüründe egemen ve eleştirel yaklaşımlara yönelik karşılaştırmalı bir alan çalışması: Lisansüstü tezler ve makaleler üzerine bibliyometrik bir analiz. Bilecik Şeyh Edebali Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 314-334. https://doi.org/10.33905/bseusbed.558321
  • Birkle, C., Pendlebury, D. A., Schnell, J. ve Adams, J. (2020). Web of Science as a data source for research on scientific and scholarly activity. Quantitative Science Studies, 1(1), 363-376. https://doi.org/10.1162/qss_a_00018
  • Chintalapati, S. ve Pandey, S. K. (2022). Artificial intelligence in marketing: A systematic literature review. International Journal of Market Research, 64(1), 38-68. https://doi.org/10.1177/14707853211018428
  • Collins, C., Dennehy, D., Conboy, K. ve Mikalef, P. (2021). Artificial intelligence in information systems research: A systematic literature review and research agenda. International Journal of Information Management, 60, 102383. https://doi.org/10.1016/j.ijinfomgt.2021.102383
  • Donthu, N., Kumar, S., Mukherjee, D., Pandey, N. ve Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
  • Emmert‐Streib, F., Yli‐Harja, O. ve Dehmer, M. (2020). Explainable artificial intelligence and machine learning: A reality rooted perspective. WIREs Data Mining and Knowledge Discovery, 10(6). https://doi.org/10.1002/widm.1368
  • Faruk, M., Rahman, M. ve Hasan, S. (2021). How digital marketing evolved over time: A bibliometric analysis on scopus database. Heliyon, 7(12), e08603. https://doi.org/10.1016/j.heliyon.2021.e08603
  • Ford, J. B., Bezbaruah, S., Mukherji, P., Jain, V. ve Merchant, A. (2021). A decade (2008–2019) of advertising research productivity: A bibliometric review. Journal of Business Research, 136, 137-163. https://doi.org/10.1016/j.jbusres.2021.07.030
  • Ghorbani, Z., Kargaran, S., Saberi, A., Haghighinasab, M., Jamali, S. M. ve Ale Ebrahim, N. (2022). Trends and patterns in digital marketing research: Bibliometric analysis. Journal of Marketing Analytics, 10(2), 158-172. https://doi.org/10.1057/s41270-021-00116-9
  • Janiesch, C., Zschech, P. ve Heinrich, K. (2021). Machine learning and deep learning. Electronic Markets, 31(3), 685-695. https://doi.org/10.1007/s12525-021-00475-2
  • José de Oliveira, O., Francisco da Silva, F., Juliani, F., César Ferreira Motta Barbosa, L., & Vieira Nunhes, T. (2019). Bibliometric method for mapping the state-of-the-art and identifying research gaps and trends in literature: An essential instrument to support the development of scientific projects. IntechOpen. 10.5772/intechopen.85856
  • Khan, H. M. R., Ahmad, S., Javed, R. ve Nasir, N. (2023). The significance of artificial intelligence in business and accounting: A bibliometric analysis. Pakistan Journal of Humanities and Social Sciences, 11(2). https://doi.org/10.52131/pjhss.2023.1102.0417
  • Kühl, N., Schemmer, M., Goutier, M. ve Satzger, G. (2022). Artificial intelligence and machine learning. Electronic Markets, 32(4), 2235-2244. https://doi.org/10.1007/s12525-022-00598-0
  • Mustak, M., Salminen, J., Plé, L. ve Wirtz, J. (2021). Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda. Journal of Business Research, 124, 389-404. https://doi.org/10.1016/j.jbusres.2020.10.044
  • Ninkov, A., Frank, J. R. ve Maggio, L. A. (2021). Bibliometrics: Methods for studying academic publishing. Perspectives on Medical Education, 11(3), 173-176. https://doi.org/10.1007/S40037-021-00695-4
  • Omar Zaki, H., Kamarulzaman, Y. ve Mohtar, M. (2020). Humour advertising: A review and a bibliometrics citation analysis. Malaysian Journal of Society and Space, 16(2). https://doi.org/10.17576/geo-2020-1602-13
  • Rasul, T., Lim, W. M., Dowling, M., Kumar, S. ve Rather, R. A. (2022). Advertising expenditure and stock performance: A bibliometric analysis. Finance Research Letters, 50, 103283. https://doi.org/10.1016/j.frl.2022.103283
  • Savaş, A. T. (2020). Dijital reklamcılık kapsamında Türkiye’de yayınlanmış lisansüstü tezlerin bibliyometrik profili. Journal of Turkish Studies, Volume 15 Issue 8(Volume 15 Issue 8), 3807-3832. https://doi.org/10.7827/TurkishStudies.46076
  • Sestino, A. ve De Mauro, A. (2022). Leveraging artificial intelligence in business: Implications, applications and methods. Technology Analysis & Strategic Management, 34(1), 16-29. https://doi.org/10.1080/09537325.2021.1883583
  • Turing, A. M. (1950). Computing machinery and intelligence. Mind, 59(236), 433-460.
  • Vakratsas, D. ve Wang, X. (Shane). (2021). Artificial ıntelligence in advertising creativity. Journal of Advertising, 50(1), 39-51. https://doi.org/10.1080/00913367.2020.1843090
  • Varsha P. S., Akter, S., Kumar, A., Gochhait, S. ve Patagundi, B. (2021). The impact of artificial intelligence on branding: A bibliometric analysis (1982-2019). Journal of Global Information Management, 29(4), 221-246. https://doi.org/10.4018/JGIM.20210701.oa10

Bibliometric Analysis of Research on Artificial Intelligence, Machine Learning and, Advertising

Yıl 2024, Sayı: 12, 114 - 147, 27.06.2024
https://doi.org/10.56676/kiad.1349868

Öz

Artificial intelligence and machine learning have an important role in meeting the complexity and rapidly changing needs of the modern world and making communication processes effective. Using AI and machine learning in advertising industry can potentially optimize more efficient, personalized, and cost-effective advertising processes. This study analyzes the bibliometric characteristics of scientific research on the Web of Science platform, which combines the fields of artificial intelligence, machine learning and advertising. The study aims to serve as a starting point for researchers and academics in artificial intelligence, machine learning, and advertising. The study’s results provide a framework for the development of the field and shed light on the most productive journals, authors, countries and institutions. The results indicate that artificial intelligence and machine learning are increasingly impacting the field of advertising. Interdisciplinary collaborations are enriching these fields, and there is a clear trend in the literature towards topics such as online advertising, social media, and big data.

Kaynakça

  • Arango Espinal, E., Ceballos Molano, R. ve Osorio Andrade, C. F. (2021). Investigación en publicidad política: Un análisis bibliométrico. Revista Guillermo de Ockham, 18(2), 181-189. https://doi.org/10.21500/22563202.4574
  • Arf, C. (1959). Makine düşünebilir mi ve nasıl düşünebilir? Atatürk Üniversitesi 1958-1959 Öğretim Yılı Halk Konferansları(1), 91-103. Batu, M. ve Yapıcıoğlu Ayaz, Y. (2021). A comparative bibliometric analysis on graduate theses in the field of public relations and advertising in Turkey. International Journal of Management Economics and Business, 17(2). https://doi.org/10.17130/ijmeb.785223
  • Becan, C. (2019). Reklamcılık literatüründe egemen ve eleştirel yaklaşımlara yönelik karşılaştırmalı bir alan çalışması: Lisansüstü tezler ve makaleler üzerine bibliyometrik bir analiz. Bilecik Şeyh Edebali Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 314-334. https://doi.org/10.33905/bseusbed.558321
  • Birkle, C., Pendlebury, D. A., Schnell, J. ve Adams, J. (2020). Web of Science as a data source for research on scientific and scholarly activity. Quantitative Science Studies, 1(1), 363-376. https://doi.org/10.1162/qss_a_00018
  • Chintalapati, S. ve Pandey, S. K. (2022). Artificial intelligence in marketing: A systematic literature review. International Journal of Market Research, 64(1), 38-68. https://doi.org/10.1177/14707853211018428
  • Collins, C., Dennehy, D., Conboy, K. ve Mikalef, P. (2021). Artificial intelligence in information systems research: A systematic literature review and research agenda. International Journal of Information Management, 60, 102383. https://doi.org/10.1016/j.ijinfomgt.2021.102383
  • Donthu, N., Kumar, S., Mukherjee, D., Pandey, N. ve Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
  • Emmert‐Streib, F., Yli‐Harja, O. ve Dehmer, M. (2020). Explainable artificial intelligence and machine learning: A reality rooted perspective. WIREs Data Mining and Knowledge Discovery, 10(6). https://doi.org/10.1002/widm.1368
  • Faruk, M., Rahman, M. ve Hasan, S. (2021). How digital marketing evolved over time: A bibliometric analysis on scopus database. Heliyon, 7(12), e08603. https://doi.org/10.1016/j.heliyon.2021.e08603
  • Ford, J. B., Bezbaruah, S., Mukherji, P., Jain, V. ve Merchant, A. (2021). A decade (2008–2019) of advertising research productivity: A bibliometric review. Journal of Business Research, 136, 137-163. https://doi.org/10.1016/j.jbusres.2021.07.030
  • Ghorbani, Z., Kargaran, S., Saberi, A., Haghighinasab, M., Jamali, S. M. ve Ale Ebrahim, N. (2022). Trends and patterns in digital marketing research: Bibliometric analysis. Journal of Marketing Analytics, 10(2), 158-172. https://doi.org/10.1057/s41270-021-00116-9
  • Janiesch, C., Zschech, P. ve Heinrich, K. (2021). Machine learning and deep learning. Electronic Markets, 31(3), 685-695. https://doi.org/10.1007/s12525-021-00475-2
  • José de Oliveira, O., Francisco da Silva, F., Juliani, F., César Ferreira Motta Barbosa, L., & Vieira Nunhes, T. (2019). Bibliometric method for mapping the state-of-the-art and identifying research gaps and trends in literature: An essential instrument to support the development of scientific projects. IntechOpen. 10.5772/intechopen.85856
  • Khan, H. M. R., Ahmad, S., Javed, R. ve Nasir, N. (2023). The significance of artificial intelligence in business and accounting: A bibliometric analysis. Pakistan Journal of Humanities and Social Sciences, 11(2). https://doi.org/10.52131/pjhss.2023.1102.0417
  • Kühl, N., Schemmer, M., Goutier, M. ve Satzger, G. (2022). Artificial intelligence and machine learning. Electronic Markets, 32(4), 2235-2244. https://doi.org/10.1007/s12525-022-00598-0
  • Mustak, M., Salminen, J., Plé, L. ve Wirtz, J. (2021). Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda. Journal of Business Research, 124, 389-404. https://doi.org/10.1016/j.jbusres.2020.10.044
  • Ninkov, A., Frank, J. R. ve Maggio, L. A. (2021). Bibliometrics: Methods for studying academic publishing. Perspectives on Medical Education, 11(3), 173-176. https://doi.org/10.1007/S40037-021-00695-4
  • Omar Zaki, H., Kamarulzaman, Y. ve Mohtar, M. (2020). Humour advertising: A review and a bibliometrics citation analysis. Malaysian Journal of Society and Space, 16(2). https://doi.org/10.17576/geo-2020-1602-13
  • Rasul, T., Lim, W. M., Dowling, M., Kumar, S. ve Rather, R. A. (2022). Advertising expenditure and stock performance: A bibliometric analysis. Finance Research Letters, 50, 103283. https://doi.org/10.1016/j.frl.2022.103283
  • Savaş, A. T. (2020). Dijital reklamcılık kapsamında Türkiye’de yayınlanmış lisansüstü tezlerin bibliyometrik profili. Journal of Turkish Studies, Volume 15 Issue 8(Volume 15 Issue 8), 3807-3832. https://doi.org/10.7827/TurkishStudies.46076
  • Sestino, A. ve De Mauro, A. (2022). Leveraging artificial intelligence in business: Implications, applications and methods. Technology Analysis & Strategic Management, 34(1), 16-29. https://doi.org/10.1080/09537325.2021.1883583
  • Turing, A. M. (1950). Computing machinery and intelligence. Mind, 59(236), 433-460.
  • Vakratsas, D. ve Wang, X. (Shane). (2021). Artificial ıntelligence in advertising creativity. Journal of Advertising, 50(1), 39-51. https://doi.org/10.1080/00913367.2020.1843090
  • Varsha P. S., Akter, S., Kumar, A., Gochhait, S. ve Patagundi, B. (2021). The impact of artificial intelligence on branding: A bibliometric analysis (1982-2019). Journal of Global Information Management, 29(4), 221-246. https://doi.org/10.4018/JGIM.20210701.oa10
Toplam 24 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular İletişim ve Medya Çalışmaları (Diğer)
Bölüm Araştırma Makaleleri
Yazarlar

Gülseli Aygül Ernek Alan 0000-0002-8522-0672

Orhan Kaan Bilgin 0000-0002-4159-8112

Yayımlanma Tarihi 27 Haziran 2024
Yayımlandığı Sayı Yıl 2024 Sayı: 12

Kaynak Göster

APA Ernek Alan, G. A., & Bilgin, O. K. (2024). Yapay Zeka, Makine Öğrenmesi ve Reklamcılık Konulu Araştırmaların Bibliyometrik Analizi. Kastamonu İletişim Araştırmaları Dergisi(12), 114-147. https://doi.org/10.56676/kiad.1349868