Decoding the Relationship of Artificial Intelligence, Advertising, and Generative Models

Author:

Lim Camille Velasco1,Zhu Yu-Peng2ORCID,Omar Muhammad3ORCID,Park Han-Woo4ORCID

Affiliation:

1. Department of Media and Communications, YeungNam University, Gyeongsan-si 38541, Republic of Korea

2. School of Journalism and Communication, Chongqing University, Chongqing 401331, China

3. Department of Computer Science, Faculty of Computing, The Islamia University of Bahawalpur, Bahawalpur 63101, Pakistan

4. Interdisciplinary Graduate Programs of Digital Convergence Business, East Asian Cultural Studies, Cyber Emotions Research Center, Big Local Big Pulse Lab, Department of Media and Communication, YeungNam University, Gyeongsan-si 38541, Republic of Korea

Abstract

Although artificial intelligence technologies have provided valuable insights into the advertising industry, more comprehensive studies that properly examine the applications of AI in advertising using scientometric network analysis are needed. Using publications from journals indexed in the Web of Science, we seek to analyze the emergence of AI through the examination of keyword co-occurrences and co-authorship. Our goal is to identify essential concepts and influential research that have significantly impacted the advertising business. The findings highlight noteworthy patterns, indicating the growing importance of machine learning tools and techniques such as deep learning, and advanced natural language processing methods like word2vec, GANs, and others, as well as their societal impacts as they continue to define the future of advertising practices.

Publisher

MDPI AG

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