A Study of Ethical Risk Issues in Computational Advertising Based on Data Algorithms
Journal: Modern Economics & Management Forum DOI: 10.32629/memf.v4i3.1369
Abstract
Algorithmic advertising independently matches and distributes advertisements, media, and users on the basis of algorithmic data, which improves the efficiency of advertising and branding, and meets the potential personalized needs of the majority of users. However, as the development of algorithmic advertising relies on the comprehensive mastery and analysis of user big data, the problem of algorithmic surveillance is becoming more and more prominent, and the hidden "bias" and "discrimination" behind the algorithm is also gradually emerging. This paper points out the problems of algorithmic neglect, bias and discrimination in computational advertising, and puts forward corresponding countermeasures to the problems arising from computational advertising, it's hoped that computational advertising can also realize benign and orderly development.
Keywords
computational advertising, big data, algorithmic surveillance
Full Text
PDF - Viewed/Downloaded: 1 TimesIndexation
Download Index RecordReferences
[1] Peng Liu, Wang Chao. Computational advertising [M]. Beijing: People's Posts and Telecommunications Press; 2015.
[2] Qingzhen Liu, Shuping Zhong. The necessity and importance of redefining the concept of computational advertising[J]. International Brand Watch. 2021; (8):2.
[3] Shuping Zhong. Reconstruction of Knowledge System and Cultivation Objectives of Advertising Disciplines in the Era of Computational Advertising[J]. Modern Communication: Journal of Communication University of China. 2021; 43(4):5.
[4] Li Zhang, Liyun Zheng. Discrimination and bias in algorithmic recommendation[J]. China Newspaper Industry. 2020;(13):2.
[5] Haichao Fan, Liping Gu. Exploring the way to balance:The practical dilemma and revision of the principle of informed consent in privacy protection[J]. Journalism and Communication Research.2021;28(02):70-85
[6] Su Liu. A Brief Discussion on User Portrait in Digital Library Knowledge Discovery System — Taking Tianjin Library as an Example[J]. Library Theory and Practice, 2017(6):4.
[7] Renhua Ou. (2022) Research on Operation Logic and Application Strategy of Smart Marketing [D]. Master's Thesis, Nanchang University, Nanchang.
[8] Yuping Xu. "Reinforcement" and "Diffusion': Panoramic Prisons under Social Media[J]. Audiovisual. 2021;(12):3.
[9] Xiangdong Xu, Yixi Wang. Causes,effects and countermeasures of algorithmic bias in intelligent communication[J]. International Journalism. 2020; 42(10):17.
[10] Kailiang Zou, Xia Wang. A preliminary study on the regulation of employment discrimination in the context of big data algorithms[J]. Price theory and practice. 2020;(6):6.
[2] Qingzhen Liu, Shuping Zhong. The necessity and importance of redefining the concept of computational advertising[J]. International Brand Watch. 2021; (8):2.
[3] Shuping Zhong. Reconstruction of Knowledge System and Cultivation Objectives of Advertising Disciplines in the Era of Computational Advertising[J]. Modern Communication: Journal of Communication University of China. 2021; 43(4):5.
[4] Li Zhang, Liyun Zheng. Discrimination and bias in algorithmic recommendation[J]. China Newspaper Industry. 2020;(13):2.
[5] Haichao Fan, Liping Gu. Exploring the way to balance:The practical dilemma and revision of the principle of informed consent in privacy protection[J]. Journalism and Communication Research.2021;28(02):70-85
[6] Su Liu. A Brief Discussion on User Portrait in Digital Library Knowledge Discovery System — Taking Tianjin Library as an Example[J]. Library Theory and Practice, 2017(6):4.
[7] Renhua Ou. (2022) Research on Operation Logic and Application Strategy of Smart Marketing [D]. Master's Thesis, Nanchang University, Nanchang.
[8] Yuping Xu. "Reinforcement" and "Diffusion': Panoramic Prisons under Social Media[J]. Audiovisual. 2021;(12):3.
[9] Xiangdong Xu, Yixi Wang. Causes,effects and countermeasures of algorithmic bias in intelligent communication[J]. International Journalism. 2020; 42(10):17.
[10] Kailiang Zou, Xia Wang. A preliminary study on the regulation of employment discrimination in the context of big data algorithms[J]. Price theory and practice. 2020;(6):6.
Copyright © 2023 Yue Ren, Lu Li, Qichen Jiang
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License