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

Autor:	Camille Velasco Lim, Yu-Peng Zhu, Muhammad Omar, Han-Woo Park
Jazyk:	angličtina
Rok vydání:	2024
Předmět:	generative AI advertising artificial intelligence advertising machine learning advertising bibliometrics full counting co-occurrence network analysis Electronic computers. Computer science QA75.5-76.95
Zdroj:	Digital, Vol 4, Iss 1, Pp 244-270 (2024)
Druh dokumentu:	article
ISSN:	2673-6470 89753054
DOI:	10.3390/digital4010013
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/5eaaffb9a55d4efdb897530541a8e5d3 Zobrazit plný text záznamu View record in DOAJ