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

Digital Pub Date : 2024-03-01 DOI:10.3390/digital4010013
Camille Velasco Lim, Yu-Peng Zhu, Muhammad Omar, H. Park
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引用次数: 0

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.
解密人工智能、广告和生成模型之间的关系
尽管人工智能技术为广告业提供了宝贵的洞察力,但仍需要进行更全面的研究,利用科学计量学网络分析对人工智能在广告业中的应用进行适当考察。我们利用《科学网》(Web of Science)收录的期刊出版物,通过考察关键词的共现和共同作者来分析人工智能的出现。我们的目标是找出对广告业务产生重大影响的基本概念和有影响力的研究。研究结果突出了值得注意的模式,表明机器学习工具和技术(如深度学习)以及高级自然语言处理方法(如 word2vec、GANs 等)的重要性与日俱增,以及它们在继续定义广告实践的未来时所产生的社会影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.10
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0.00%
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