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Reklam ve Yapay Zeka İlişkisi: “Journal of Advertising" Dergisindeki Makalelerin Bibliyometrik Analizi

Yıl 2024, Cilt: 11 Sayı: 21, 104 - 126, 29.12.2024
https://doi.org/10.56133/intermedia.1533851

Öz

Yapay zeka teknolojisinin hızla yayılması, insan iş gücünün azaltılmasına ve sonuç odaklı çalışmaların daha pratik yapılmasına zemin hazırlamıştır. Bu durum yapay zekanın reklamcılık sektöründe de yer edinmeye başlamasını sağlamıştır. Yapay zekanın reklam süreci üzerindeki etkisi, reklam alanında yeniden bir yapılanmanın olabileceği düşüncesini doğurmaktadır. Geleneksel reklam çalışmalarına kıyasla yapay zeka kullanılarak oluşturulan reklamların bazı avantaj ve dezavantajları da beraberinde getirdiğini söylemek mümkündür. Yeni sayabileceğimiz bu kavramın reklam alanyazındaki konumunu bilmek gerekmektedir. Reklamcılık alanında yapay zeka ile ilgili bilimsel çalışmaların analizi, reklamda yapay zeka kullanımının gelişimi ve gelecekteki araştırmalar için çeşitli potansiyel yollar sunması açısından önemlidir. Bu araştırmada, Social Sciences Citation Index’te taranan “Journal of Advertising” dergisinde yayınlanan reklam ve yapay zeka makaleleri bibliyometrik analizle incelenmiştir. Araştırmanın amacı bibliyometrik ve çerçeveye dayalı bir analiz yaparak reklamda yapay zeka kullanımının gelişimini ortaya koymaktır. Araştırma sonucunda dergide konuyla ilgili ilk makalenin 2019 yılında yayınlandığı ve makalelerde, reklamda yapay zeka kullanımının daha çok teorik olarak ele alındığı görülmüştür. Yapılan analiz ile makalelerin daha çok programatik reklamcılık, hesaplamalı reklamcılık, çevrimiçi reklamlar, yapay zeka ile üretilen reklamlar, dijital veriler, chatbot reklamları ve yapay zeka Influencerları çerçevesinde şekillendiği ve incelendiği gözlemlenmiştir.

Kaynakça

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  • Adaş, E. B. & Erbay, B. (2021). Yapay Zekâ Sosyolojisi Üzerine Bir Değerlendirme. Gaziantep Üniversitesi Journal of Social Sciences, 21(1), 326-337. https://doi.org/10.21547/jss.991383.
  • Arango, L., Singaraju, S. P. & Niininen, O. (2023). Consumer Responses to AI-Generated Charitable Giving Ads. Journal of Advertising, 52(4), 1-18. https://doi.org/10.1080/00913367.2023.2183285.
  • Araujo, T., Copulsky, J. R., Hayes, J. L., Kim, S. J. & Srivastava, J. (2020). From Purchasing Exposure to Fostering Engagement: Brand-Consumer Experiences in The Emerging Computational Advertising Landscape. Journal of Advertising, 49(4), 428-445. https://doi.org/10.1080/00913367.2020.1795756
  • Bozkurt, Ö. Ç. & Çetin, A. (2016). Girişimcilik ve Kalkınma Dergisi’nin Bibliyometrik Analizi. Girişimcilik ve Kalkınma Dergisi, 11(2), 229- 263.
  • Butow, P. & Hoque, E. (2020). Using Artificial İntelligence to Analyse and Teach Communication in Healthcare. The Breast, 50, 49-55. https://doi.org/10.1016/j.breast.2020.01.008
  • Campbell, C., Plangger, K., Sands, S. & Kietzmann, J. (2022). Preparing For an Era of Deepfakes and AI-Generated Ads: A Framework For Understandin Responses to Manipulated Advertising. Journal of Advertising, 51(1), 22-38. https://doi.org/10.1080/00913367.2021.1909515
  • Campbell, C., Sands, S., Montecchi, M. & Schau, H. J. (2022). That’s So Instagrammable. Understanding How Environments Generate Indirect Advertising By Cueing Consumer-Generated Content. Journal of Advertising, 51(4), 411-429. https://doi.org/10.1080/00913367.2022.2053901
  • Chen, G., Xie, P., Dong, J. & Wang, T. (2019). Understanding Programmatic Creative: The Role of AI. Journal of Advertising, 48(4), 347-355. https://doi.org/10.1080/00913367.2019.1654421
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  • Cueto González, M., Parreño Fernández, J., de la Fuente García, D. & Gómez Gómez, A. (2023). Machine Learning in Online Advertising Research: A Systematic Mapping Study. L.R. Izquierdo, J.I. Santos, J.J. Lavios, & V. Ahedo içinde, Industry 4.0: The Power of Data. Lecture Notes in Management and Industrial Engineering. Springer, Cham.
  • Deng, S., Tan, C., Wang, W. & Pan, Y. (2019). Smart Generation System of Personalized Advertising Copy and Its Application to Advertising Practise and Research. Journal of Advertising, 48(4), 356-365. https://doi.org/10.1080/00913367.2019.1652121
  • Donthu, N., Kumar, S. & Pattnaik, D. (2020). Forty-five Years of Journal of Business Research: A Bibliometric Analysis. Journal of Business Research, 109(2020), 1-14. https://doi.org/10.1016/j.jbusres.2019.10.039
  • Donthu, N., Kumar, S., Mukherjee, D., Pandey, N. & 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
  • Erkan, İ. (2020). Dijital Pazarlamanın Dünü, Bugünü, Geleceği: Bibliyometrik Bir Analiz. Akademik Hassasiyetler, 7(13), 149-168.
  • Erşanlı Taş, B. (2023). Tasarımcının Yapay Zekâ İle İmtihanı. Yeni Medya Çalışmaları VI. Ulusal Kongresi 16-17 Kasım Program ve Bildiri Özetleri Kitabı (s.146-147). Eskişehir: Alternatif Bilişim Derneği. https://yenimedya.org.tr/content/ozet-kitabi
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Relationship Between Advertising and Artificial Intelligence: Bibliometric Analysis of Articles In The “Journal of Advertising"

Yıl 2024, Cilt: 11 Sayı: 21, 104 - 126, 29.12.2024
https://doi.org/10.56133/intermedia.1533851

Öz

The rapid spread of artificial intelligence technology has paved the way for a reduction in the human workforce and more practical result-oriented work. This situation has enabled artificial intelligence to gain a place in the advertising sector. The impact of artificial intelligence on the advertising process gives rise to the idea that there may be a restructuring in the field of advertising. Compared to traditional advertising studies, it is possible to say that advertisements created using artificial intelligence bring along some advantages and disadvantages. It is necessary to know the position of this new concept in the advertising literature. The analysis of scientific studies on artificial intelligence in advertising is important in terms of the development of the use of artificial intelligence in advertising and offering various potential avenues for future research. In this study, artificial intelligence in advertising articles published in the "Journal of Advertising", which is scanned in the Social Sciences Citation Index, were analyzed by bibliometric analysis. The aim of the research is to reveal the development of the use of artificial intelligence in advertising by conducting a bibliometric and framework-based analysis. As a result of the research, it was observed that the first article on the subject in the journal was published in 2019 and the use of artificial intelligence in advertising was mostly theoretical. With the analysis, it was observed that the articles were mostly shaped and examined within the framework of programmatic advertising, computational advertising, online ads, ads produced with artificial intelligence, digital data, chatbot ads and artificial intelligence influencers.

Kaynakça

  • Acar, H. M. & Tanyıldızı, N. İ. (2022). Reklamda Yapay Zekâ Kullanımı: Ziraat Bankası #Senhepgülümse Reklam Filminde Deepfake Uygulamasının Görsel Anlatıya Etkisi. Kastamonu İletişim Araştırmaları Dergisi, (8), 78-99.
  • Adaş, E. B. & Erbay, B. (2021). Yapay Zekâ Sosyolojisi Üzerine Bir Değerlendirme. Gaziantep Üniversitesi Journal of Social Sciences, 21(1), 326-337. https://doi.org/10.21547/jss.991383.
  • Arango, L., Singaraju, S. P. & Niininen, O. (2023). Consumer Responses to AI-Generated Charitable Giving Ads. Journal of Advertising, 52(4), 1-18. https://doi.org/10.1080/00913367.2023.2183285.
  • Araujo, T., Copulsky, J. R., Hayes, J. L., Kim, S. J. & Srivastava, J. (2020). From Purchasing Exposure to Fostering Engagement: Brand-Consumer Experiences in The Emerging Computational Advertising Landscape. Journal of Advertising, 49(4), 428-445. https://doi.org/10.1080/00913367.2020.1795756
  • Bozkurt, Ö. Ç. & Çetin, A. (2016). Girişimcilik ve Kalkınma Dergisi’nin Bibliyometrik Analizi. Girişimcilik ve Kalkınma Dergisi, 11(2), 229- 263.
  • Butow, P. & Hoque, E. (2020). Using Artificial İntelligence to Analyse and Teach Communication in Healthcare. The Breast, 50, 49-55. https://doi.org/10.1016/j.breast.2020.01.008
  • Campbell, C., Plangger, K., Sands, S. & Kietzmann, J. (2022). Preparing For an Era of Deepfakes and AI-Generated Ads: A Framework For Understandin Responses to Manipulated Advertising. Journal of Advertising, 51(1), 22-38. https://doi.org/10.1080/00913367.2021.1909515
  • Campbell, C., Sands, S., Montecchi, M. & Schau, H. J. (2022). That’s So Instagrammable. Understanding How Environments Generate Indirect Advertising By Cueing Consumer-Generated Content. Journal of Advertising, 51(4), 411-429. https://doi.org/10.1080/00913367.2022.2053901
  • Chen, G., Xie, P., Dong, J. & Wang, T. (2019). Understanding Programmatic Creative: The Role of AI. Journal of Advertising, 48(4), 347-355. https://doi.org/10.1080/00913367.2019.1654421
  • Chuan, C., Tsai, W. S. & Yang, J. (2023). Artificial Intelligence, Advertising and Society. Advertising & Society Quarterly, 24(3). 10.1353/asr.2023.a911198
  • Coffin, J. (2022). Asking Questions of AI Advertising: A Maieutic Approach. Journal of Advertising, 51(5), 608-623. https://doi.org/10.1080/00913367.2022.2111728
  • Cueto González, M., Parreño Fernández, J., de la Fuente García, D. & Gómez Gómez, A. (2023). Machine Learning in Online Advertising Research: A Systematic Mapping Study. L.R. Izquierdo, J.I. Santos, J.J. Lavios, & V. Ahedo içinde, Industry 4.0: The Power of Data. Lecture Notes in Management and Industrial Engineering. Springer, Cham.
  • Deng, S., Tan, C., Wang, W. & Pan, Y. (2019). Smart Generation System of Personalized Advertising Copy and Its Application to Advertising Practise and Research. Journal of Advertising, 48(4), 356-365. https://doi.org/10.1080/00913367.2019.1652121
  • Donthu, N., Kumar, S. & Pattnaik, D. (2020). Forty-five Years of Journal of Business Research: A Bibliometric Analysis. Journal of Business Research, 109(2020), 1-14. https://doi.org/10.1016/j.jbusres.2019.10.039
  • Donthu, N., Kumar, S., Mukherjee, D., Pandey, N. & 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
  • Erkan, İ. (2020). Dijital Pazarlamanın Dünü, Bugünü, Geleceği: Bibliyometrik Bir Analiz. Akademik Hassasiyetler, 7(13), 149-168.
  • Erşanlı Taş, B. (2023). Tasarımcının Yapay Zekâ İle İmtihanı. Yeni Medya Çalışmaları VI. Ulusal Kongresi 16-17 Kasım Program ve Bildiri Özetleri Kitabı (s.146-147). Eskişehir: Alternatif Bilişim Derneği. https://yenimedya.org.tr/content/ozet-kitabi
  • Franke, C., Groeppel-Klein, A. & Müller, K. (2023). Consumers’ Responses to Virtual Influencers As Advertising Endorsers: Novel and Effective or Uncanny and Deceiving?. Journal of Advertising, 52(4), 523-539. https://doi.org/10.1080/00913367.2022.2154721
  • Gunkel, D. J. (2012). Communication and Artificial Intelligence: Opportunities and Challenges For The 21st Century. communication+ 1, 1(1), 1-26.
  • Guzman, A. L. & Lewis, S. C. (2020). Artificial Intelligence and Communication: A Human–Machine Communication Research Agenda. New Media & Society, 22(1), 70-86. https://doi.org/10.1177/1461444819858691
  • Güngör, A. & Pınarbaşı, T. E. (2023). Alanyazında Bir İkilem: Yapay Zeka, Yeni Medya ve İletişim Pratiklerine Dair Bir Tartışma. C. Yaşın ve H. Hülür içinde, İletişim ve kültürün dijital dönüşümü pratikler ve süreçler (s. 71-90). Ankara: Ütopya Yayınevi.
  • Ha, Y., Park, K., Kim, S. J., Joo, J. & Cha, M. (2021). Automatically Detecting Image-Text Mismatch on Instagram With Deep Learning. Journal of Advertising, 50(1), 52-62. https://doi.org/10.1080/00913367.2020.1843091
  • Hayes, J. L., Britt, B. C., Evans, W., Rush, S. W., Towery, N. A. & Adamson, A. C. (2021). Can Social Media Listening Platforms’ Artificial Intelligence Be Trusted? Examining The Accuracy of Crimson Hexagon’s (Now Brandwatch Consumer Research’s) Al-Driven Analyses. Journal of Advertising, 50(1), 81-91. https://doi.org/10.1080/009133 67.2020.1809576
  • Helberger, N., Huh, J., Milne, G., Strycharz, J. & Sundaram, H. (2020). Macro and Exogenous Factors in Computational Advertising: Key Issues and New Research Directions. Journal of Advertising, 49(4), 377-393. https://doi.org/10.1080/00913367.2020.1811179
  • Hohenstein, J., Kizilcec, R. F., Difranzo, D., Aghajari, Z., Mieczkowski, H., Levy, K., Naaman, M. & Jung, M. F. (2023). Artificial Intelligence in Communication Impacts Language and Social Relationships. Scientific Reports, 13(1), 1-9. 10.1038/s41598-023-30938-9
  • Jin, S., Lin, W., Yin, H., Yang, S., Li A. & Deng, B. (2015). Community Structure Mining in Big Data Social Media Networks with MapReduce. Cluster Computing, 18(3), 999–1010. https://doi.org/10.1007/s10586-015-0452-x
  • Jones, N. & Hamby, A. (2023). It’s Written on Your Face: How Emotional Variation in Super Bowl Advertisements Influences Ad Liking. Journal of Advertising, 53(3), 463-472. https://doi.org/10.1080/00913367.2023.2218896
  • Kaplan, A. & Haenlein, M. (2019). Siri, Siri in My Hand, Who is The Fairest in The Land? On The Interpretations, Illustrations And Implications of Artifcial Intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j. bushor.2018.08.004
  • Karnouskos, S. (2020). Artificial Intelligence in Digital Media: The Era of Deepfakes. Ieee Transactions on Technology and Society, 1(3), 138-147. 10.1109/TTS.2020.3001312
  • Kerlinger, F. N. & Lee, H. B. (1999). Foundations Of Behavioral Research. Boston: Harcourt College.
  • Kietzmann, J., Paschen, J. & Treen, E. (2018). Artificial Intelligence in Advertising: How Marketers Can Leverage Artificial Intelligence Along The Consumer Journey. Journal of Advertising Research, 58(3), 263-267. 10.2501/JAR-2018-035
  • Kim, S. J. (2023). A Scoping Review of Emotion AI in Advertising Research and Practise: Opportunities and Challenges Ahead. Global Marketing Conference Temmuz (s.859-860). Seoul: Global Alliance of Marketing & Management Associations.
  • Kim, W., Ryoo, Y., Lee, S. & Lee, J. A. (2023). Chatbot Advertising As A Double-Edged Sword: The Roles of Regulatory Focus and Privacy Concerns. Journal of Advertising, 52(4), 504-522. https://doi.org/10.1080/00913367.2022.2043795
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  • Koçyiğit, A. & Darı, A. B. (2023). Yapay Zeka İletişiminde ChatGpt: İnsanlaşan Dijitalleşmenin Geleceği. Stratejik ve Sosyal Araştırmalar Dergisi, 7(2), 427-438. https://doi.org/10.30692/sisad.1311336
  • Latar, N. L. (2021). Sosyal Fizik Çağında Robot Gazeteci-İnsan Gazeteciliğinin Sonu Mu?. F. Zengin ve B. Kapır içinde, Yapay zeka ve media (s 193-216). İstanbul: Doruk Yayıncılık.
  • Lee, M. H., Kim, S. J., Yoon, S. & Park, S. (2022). An Integrative Approach to Determinants of Pre-Roll Ad Acceptance and Their Relative Impact: Evidence From Big Data. Journal of Advertising, 51(1), 76-84. https://doi.org/10.1080/00913367.2021.1932643
  • Li, H. (2019). Special Section Introduction: Artificial Intelligence and Advertising. Journal of Advertising, 48(4), 333-337. https://doi.org/10.1080/00913367.2019.1654947
  • Liao, M. & Sundar S. S. (2022). When E-Commerce Personalization Systems Show and Tell: Investigating The Relative Persuasive Appeal of Content-Based Versus Collaborative Filtering. Journal of Advertising, 51(2), 256-267. https://doi.org/10.1080/00913367.2021.1887013
  • Lou, C., Kiew, S. T. J., Chen, T., Lee, T. Y. M., Ong, J. E. C. & Phua, Z. (2022). Authentically Fake? How Consumers Respond to The Influence of Virtual Influencers. Journal of Advertising, 52(4), 540-557. https://doi.org/10.1080/ 00913367.2022.2149641
  • Lv, L. & Huang, M. (2022). Can Personalized Recommendations in Charity Advertising Boost Donation? The Role of Perceived Autonomy. Journal of Advertising, 53(1), 36-53. https://doi.org/10.1080/00913367.2022.2109082
  • Malthouse, E. C., Hessary, Y. K., Vakeel, K. A., Burke, R. & Fudurić, M. (2019). An Algorithm For Allocating Sponsored Recommendations and Content: Unifying Programmatic Advertising and Recommender Systems. Journal of Advertising, 48(4), 366-379. https://doi.org/10.1080/00913367.2019.1652123
  • Oxford Reference (ty). Artificial intelligence. 14.01.2024 tarihinde https://www.oxfordreference.com/display/10.1093/oi/authority.20110803095426960 adresinden erişilmiştir.
  • Pahari, S., Bandyopadhyay, A., V. M., V. K. & Pingle, S. (2024). A Bibliometric Analysis of Digital Advertising in Social Media: The State of the Art and Future Research Agenda. Cogent Business & Management, 11(1), 1-24. https://doi.org/10.1080/23311975.2024.2383794
  • Pannu, A. (2015). Artificial Intelligence and Its Application in Different Areas. International Journal of Engineering and Innovative Technology (IJEIT), 4(10), 79–84.
  • Prihatiningsih, T., Panudju, R. & Prasetyo, I. J. (2025). Digital Advertising Trends and Effectiveness in the Modern Era: A Systematic Literatüre Review. Golden Ratio of Marketing and Applied Psychology of Business, 5(1), 1-12. https://doi.org/10.52970/grmapb.v5i1.505
  • Qin, X. & Jiang, Z. (2019). The Impact of AI on The Advertising Process: The Chinese Experience. Journal of Advertising, 48(4), 338–346. https://doi.org/10.1080/00913367.2019.1652122
  • Rodgers, S. (2021). Themed Issue Introduction: Promises and Perils of Artificial Intelligence and Advertising. Journal of Advertising, 50(1), 1-10. https://doi.org/10.1080/00913367.2020.1868233
  • Rodgers, W. & Nguyen, T. (2022). Advertising Benefits From Ethical Artificial Intelligence Algorithmic Purchase Decision Pathways. Journal of Business Ethics, 178(4), 1043-1061. https://doi.org/10.1007/s10551-022-05048-7
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  • Thomas, V. L. & Fowler, K. (2021). Close Encounters of The AI Kind: Use of AI Influencers As Brand Endorsers. Journal of Advertising, 50(1), 11-25. https://doi.org/10.1080/00913367.2020.1810595
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  • Vakratsas, D. & Wang, X. (2021). Artificial Intelligence in Advertising Creativity. Journal of Advertising, 50(1), 39-51. https://doi.org/10.1080/00913367.2020.1843090
  • van Esch, P., Cui, Y. G. & Jain, S. P. (2021). Stimulating or Intimidating: The Effect of Al-Enabled In-Store Communication on Consumer Patronage Likelihood. Journal of Advertising, 50(1), 63-80. https://doi.org/10.1080/00913367.2020.1832939
  • van Noort, G., Himelboim, I., Martin, J. & Collinger, T. (2020). Introducing A Model of Automated Brand-Generated Content in An Era of Computational Advertising. Journal of Advertising, 49(4), 411-427. https://doi.org/10.1080/00913367.2020.1795954
  • Verma, S. & Gustafsson, A. (2020). Investigating The Emerging COVID-19 Research Trends in The Field of Business and Management: A Bibliometric Analysis Approach. Journal of Business Research, 118, 253-261. https://doi.org/10.1016/j.jbusres.2020.06.057
  • von Hoffman, C. (2022, 19 Ekim). What Every Marketer Needs to Know About Programmatic Advertising. 14.01.2024 tarihinde https://martech.org/what-you-need-to-know-about-programmatic-advertising/ adresinden erişilmiştir.
  • Watts, J. & Adriano, A. (2021). Uncovering The Sources of Machine-Learning Mistakes in Advertising: Contextual Bias in The Evaluation of Semantic Relatedness. Journal of Advertising, 50(1), 26-38. https://doi.org/10.1080/00913367.2020.1821411
  • Westerlund, M. (2019). The Emergence of Deepfake Technology: A Review. Technology Innovation Management Review, 9(11), 39-52. https://doi.org/10.22215/timreview/1282
  • Yun, J. T., Segijn, C. M., Pearson, S., Malthouse, E. C., Konstan, J. A. & Shankar, V. (2020). Challenges and Future Directions of Computational Advertising Measurement Systems. Journal of Advertising, 49(4), 446-458. https://doi.org/10.1080/00913367.2020.1795757
Toplam 65 adet kaynakça vardır.

Ayrıntılar

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

Arzu Güngör 0000-0001-9615-1978

Nural İmik Tanyıldızı 0000-0002-9177-759X

Erken Görünüm Tarihi 27 Aralık 2024
Yayımlanma Tarihi 29 Aralık 2024
Gönderilme Tarihi 15 Ağustos 2024
Kabul Tarihi 29 Kasım 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 11 Sayı: 21

Kaynak Göster

APA Güngör, A., & İmik Tanyıldızı, N. (2024). Reklam ve Yapay Zeka İlişkisi: “Journal of Advertising" Dergisindeki Makalelerin Bibliyometrik Analizi. Intermedia International E-Journal, 11(21), 104-126. https://doi.org/10.56133/intermedia.1533851

Creative Commons Lisansı Intermedia International E-journal

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