A survey of online video advertising

IF 6.4 2区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery Pub Date : 2023-01-18 DOI:10.1002/widm.1489

Haijun Zhang, Xiangyu Mu, Han Yan, Lang Ren, Jianghong Ma

引用次数: 0

Abstract

With the development of social media and the ubiquity of the Internet, recent years have witnessed the rapid development of online video advertising among publishers and advertisers. Video advertising, as a new type of advertisement, has gained significant research attention from both academia and industry, coinciding with the ever‐growing volume of online videos. In this research, we provide a comprehensive survey of online video advertising in the fields of social science and computer science. We investigate state‐of‐the‐art articles from 1990 to the present and provide a new taxonomy of extant research topics based on these articles. We also highlight the factors that cause advertising to affect people and the most popular video advertising techniques used in computer science. Finally, on the basis of the analytics of the surveyed papers, future challenges are identified and potential solutions to these are discussed.

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在线视频广告调查

随着社交媒体的发展和互联网的普及，近年来网络视频广告在发布商和广告主中得到了迅速的发展。视频广告作为一种新型的广告形式，随着网络视频数量的不断增长，越来越受到学术界和产业界的关注。在这项研究中，我们提供了一个全面的调查在线视频广告在社会科学和计算机科学领域。我们调查了从1990年到现在的最先进的文章，并在这些文章的基础上对现有的研究主题进行了新的分类。我们还强调了导致广告影响人们的因素以及计算机科学中最流行的视频广告技术。最后，在分析调查论文的基础上，确定了未来的挑战，并讨论了这些挑战的潜在解决方案。

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

Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

22.70

自引率

2.60%

发文量

审稿时长

>12 weeks

期刊介绍： The goals of Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (WIREs DMKD） are multifaceted. Firstly, the journal aims to provide a comprehensive overview of the current state of data mining and knowledge discovery by featuring ongoing reviews authored by leading researchers. Secondly, it seeks to highlight the interdisciplinary nature of the field by presenting articles from diverse perspectives, covering various application areas such as technology, business, healthcare, education, government, society, and culture. Thirdly, WIREs DMKD endeavors to keep pace with the rapid advancements in data mining and knowledge discovery through regular content updates. Lastly, the journal strives to promote active engagement in the field by presenting its accomplishments and challenges in an accessible manner to a broad audience. The content of WIREs DMKD is intended to benefit upper-level undergraduate and postgraduate students, teaching and research professors in academic programs, as well as scientists and research managers in industry.