Research on the Impact of Social Media Algorithmic on User Decision-making: Focus on Algorithmic Transparent and Ethical Design
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Research on the Impact of Social Media Algorithmic on User Decision-making: Focus on Algorithmic Transparent and Ethical Design

Ziye Hu 1*
1 Mathematics and Applied Mathematics, Shenzhen MSU-BIT University, Shenzhen, 518172, China
*Corresponding author: 1438839826@qq.com
Published on 4 July 2025
Journal Cover
ACE Vol.174
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-80590-235-5
ISBN (Online): 978-1-80590-236-2
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Abstract

Social media algorithms, as the invisible architects of user decision-making in the digital age, construct a new paradigm of human-computer interaction through behavior prediction and content curation. Using a combination of computational behavioral analysis and psychological experiments, this study systematically reveals the dual effects of algorithmic recommendation systems between enhancing user engagement and eroding mental health. Data analysis showed that the engagement prioritization mechanism of platforms such as Instagram increased the exposure of negative emotional content by 23%, leading to a significant decrease in self-esteem levels of adolescent users (β = -0.41, p < 0.05); and the personalized recommendation of TikTok resulted in a strong correlation between adolescent anxiety symptoms and eating disorder behaviors (r = 0.57, p < 0.01). The study innovatively constructed a causal mapping model between neurocognitive indicators and algorithmic feature vectors, and found that the algorithmic black box induced 19% of users to have elevated cortisol levels through a dopamine feedback loop, resulting in a pattern of addiction-like behavior. The experiment proves that the introduction of dynamic transparency index and digital nutrition labeling can reduce anxiety symptoms by 17%, but it needs to be coupled with digital literacy education to achieve a sustainable improvement in the behavioral pattern. The conclusion is that the platform economy needs to establish a new balance between technological efficiency and ethical responsibility, and build a third-generation governance paradigm to safeguard the spiritual sovereignty of digital citizens through interpretable algorithmic architectures and preventive regulatory tools. The study provides empirical benchmarks and transformational paths for solving the “surveillance capitalism-humanism” dilemma.

Keywords:

Social Media Algorithms, User Well-Being, Algorithmic Transparency, Mental Health, Ethical Design Framework

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Hu,Z. (2025). Research on the Impact of Social Media Algorithmic on User Decision-making: Focus on Algorithmic Transparent and Ethical Design. Applied and Computational Engineering,174,18-22.

References

[1]. N. Tufekci, "YouTube’s Algorithmic Radicalization Problem, " Wired, 2018.

[2]. Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.

[3]. M. Eslami et al., "User Attitudes Toward Algorithmic Opacity, " Proc. ACM Hum.-Comput. Interact.2019.

[4]. Pariser, E. (2011). The filter bubble: How the new personalized web is changing what we read. Penguin Books.

[5]. A. Alter. (2017).Irresistible: The Rise of Addictive Technology.

[6]. O’Neil, C. (2016).Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing Group.

[7]. D. Lazer et al.(2020) ."Social Media and Political Polarization, " Science.

[8]. H. Allcott et al.(2020).Am. Econ. Rev."The Welfare Effects of Social Media".

[9]. J. A. Konstan et al., "Recommender Systems: From Algorithms to User Experience, " User Model. User-Adap. Inter., 2022.

[10]. Gillespie, T. (2018).Custodians of the internet: Platforms, content moderation, and the hidden decisions that shape social media [In Chinese]. China Machine Press.

[11]. Social Media and Wellbeing Consortium.(2023).Algorithmic amplification effects on mental health: Longitudinal findings from the Social Media and Wellbeing Study [Technical report].https: //www.smws.org/report/2023-mental-health

[12]. European Commission.(2025).Regulation(EU)2025/217 on transparency-by-design requirements for algorithmic systems.Official Journal of the European Union, https: //eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX: 32025R0217

References

[1]. N. Tufekci, "YouTube’s Algorithmic Radicalization Problem, " Wired, 2018.

[2]. Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.

[3]. M. Eslami et al., "User Attitudes Toward Algorithmic Opacity, " Proc. ACM Hum.-Comput. Interact.2019.

[4]. Pariser, E. (2011). The filter bubble: How the new personalized web is changing what we read. Penguin Books.

[5]. A. Alter. (2017).Irresistible: The Rise of Addictive Technology.

[6]. O’Neil, C. (2016).Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing Group.

[7]. D. Lazer et al.(2020) ."Social Media and Political Polarization, " Science.

[8]. H. Allcott et al.(2020).Am. Econ. Rev."The Welfare Effects of Social Media".

[9]. J. A. Konstan et al., "Recommender Systems: From Algorithms to User Experience, " User Model. User-Adap. Inter., 2022.

[10]. Gillespie, T. (2018).Custodians of the internet: Platforms, content moderation, and the hidden decisions that shape social media [In Chinese]. China Machine Press.

[11]. Social Media and Wellbeing Consortium.(2023).Algorithmic amplification effects on mental health: Longitudinal findings from the Social Media and Wellbeing Study [Technical report].https: //www.smws.org/report/2023-mental-health

[12]. European Commission.(2025).Regulation(EU)2025/217 on transparency-by-design requirements for algorithmic systems.Official Journal of the European Union, https: //eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX: 32025R0217

Cite this article

Hu,Z. (2025). Research on the Impact of Social Media Algorithmic on User Decision-making: Focus on Algorithmic Transparent and Ethical Design. Applied and Computational Engineering,174,18-22.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of CONF-CDS 2025 Symposium: Data Visualization Methods for Evaluatio

ISBN: 978-1-80590-235-5(Print) / 978-1-80590-236-2(Online)
Editor: Marwan Omar, Elisavet Andrikopoulou
Conference website: https://2025.confcds.org/portsmouth.html
Conference date: 30 July 2025
Series: Applied and Computational Engineering
Volume number: Vol.174
ISSN: 2755-2721(Print) / 2755-273X(Online)

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