Analisis Bibliometrik Integrasi Kecerdasan Buatan dalam Pemasaran Media Sosial: Tren Terkini dan Agenda Riset Masa Depan

Authors

  • Ratna Dewi Fakultas Ekonomi dan Bisnis, Universitas Muslim Indonesia, Makassar
  • Rastina Kalla Mansyur Fakultas Ekonomi dan Bisnis, Universitas Muslim Indonesia, Makassar
  • Rahmad Solling Hamid Universitas Ekonomi dan Bisnis, Universitas Muhammadiyah Palopo, Palopo

DOI:

https://doi.org/10.47747/snfmi.v3i1.3161

Abstract

This bibliometric analysis is a collaborative effort that explores the integration of Artificial Intelligence (AI) in social media marketing, with a focus on publications from 2015 to 2024. Drawing on the Scopus and Web of Science databases, the study identifies the most influential authors, journals, institutions, and countries, and assesses productivity, impact, and collaboration patterns in this research domain. The findings reveal a significant growth in this field, with an annual growth rate of 40.98% and an average of 32.13 citations per document, confirming the growing academic interest in the application of AI in social media marketing. The study highlights key trends, such as the rise of AI-generated influencers and the use of predictive analytics to optimize marketing strategies. These results, a testament to our collective efforts, provide valuable insights for academics and practitioners and suggest future research directions that explore the social, ethical, and economic implications of AI in marketing, with a particular focus on small and medium-sized enterprises (SMEs). This paper advances the theory and practice of AI-based digital marketing by providing a comprehensive overview of the current landscape and suggesting avenues for further research.

References

Chatterjee, S., Rana, N. P., Tamilmani, K., Sharma, A., & Dwivedi, Y. K. (2023). Artificial intelligence in marketing: A review and research agenda. Journal of Business Research, 156, 113457.

Dwivedi, Y. K., Hughes, D. L., Coombs, C., Constantiou, I., Duan, Y., Edwards, J. S., ... & Wade, M. R. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994.

Ferraro, C., Pizzetti, M., Michelini, L., & Venuti, F. (2022). Unreal influence: Leveraging AI in influencer marketing. European Journal of Marketing, 56(1), 208–231.

Gupta, S., Leszkiewicz, A., Kumar, V., Bijmolt, T., & Potapov, D. (2020). Digital analytics: Modeling for insights and new methods. Journal of interactive marketing, 51(1), 26-43.

Hossain, M. A., Agnihotri, R., Rushan, M. R. I., Rahman, M. S., & Sumi, S. F. (2022). Marketing analytics capability, artificial intelligence adoption, and firms' competitive advantage: Evidence from the manufacturing industry. Industrial Marketing Management, 106, 240-255.

Kumar, V., & Reinartz, W. (2016). Creating Enduring Customer Value. Journal of Marketing, 80(6), 36–68.

Moncrief, W. C. (2017). Are sales as we know it dying… or merely transforming?. Journal of Personal Selling & Sales Management, 37(4), 271-279.

Pahari, S., Bandyopadhyay, A., VM, 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), 2383794.

Rusthollkarhu, S., Toukola, S., Aarikka-Stenroos, L., & Mahlamäki, T. (2022). Managing B2B customer journeys in digital era: Four management activities with artificial intelligence-empowered tools. Industrial Marketing Management, 104, 241-257.

Salminen, J., Mustak, M., Corporan, J., Jung, S. G., & Jansen, B. J. (2022). Detecting pain points from user-generated social media posts using machine learning. Journal of Interactive Marketing, 57(3), 517-539.

Sands, S., Campbell, C. L., Plangger, K., & Ferraro, C. (2022). Unreal influence: leveraging AI in influencer marketing. European Journal of Marketing, 56(6), 1721-1747.

Sands, S., Ferraro, C., Demsar, V., & Chandler, G. (2022). False idols: Unpacking the opportunities and challenges of falsity in the context of virtual influencers. Business Horizons, 65(6), 777-788.

Wang, R., Luo, J., & Huang, S. S. (2020). Developing an artificial intelligence framework for online destination image photos identification. Journal of Destination Marketing & Management, 18, 100512.

Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429–472.

Downloads

Published

2025-11-09