AI-driven Personalization on Social Media: Enhancing User Experience or Invasion of Privacy
Research Article
Open Access
CC BY

AI-driven Personalization on Social Media: Enhancing User Experience or Invasion of Privacy

Yuxuan Li 1*
1 Jinan Foreign Language School
*Corresponding author: li.yaungyaung@gmail.com
Published on 11 July 2025
Volume Cover
LNEP Vol.108
ISSN (Print): 2753-7056
ISSN (Online): 2753-7048
ISBN (Print): 978-1-80590-277-5
ISBN (Online): 978-1-80590-278-2
Download Cover

Abstract

The primary goal of this research is to investigate the benefits and risks associated with AI-driven personalization on social media platforms. This technology enhances user experiences by expanding services, increasing user engagement, and improving the economic value of platforms. However, it also introduces challenges, such as limiting user choice and potentially worsening decision-making. The study also examines the risk of privacy invasion, particularly when users cannot access or control their personal data. The objective of this research is to inform policymakers about the need for enhanced data security regulations. Social media platforms should empower users with greater control over their data and be more transparent about its use. Individuals must also exercise caution in sharing personal information online.

Keywords:

AI-driven personalization technology, social media, privacy invasion

View PDF
Li,Y. (2025). AI-driven Personalization on Social Media: Enhancing User Experience or Invasion of Privacy. Lecture Notes in Education Psychology and Public Media,108,34-39.

References

[1]. Pai, C. K. , Liu, Y. , Kang, S. , Dai, A. (2020) The role of perceived smart tourism technology experience for tourist satisfaction, happiness and revisit intention. Sustainability, 12(16):6592.

[2]. Donahue, M. (2021) " Times They Are a Changin"-Can the Ad Tech Industry Survive in a Privacy Conscious World?. Cath. UJL & Tech, 30: 193.

[3]. Davenport, T. , Kalakota, R. (2019) The potential for artificial intelligence in healthcare. Future healthcare journal, 6(2): 94-98.

[4]. Yu, J. , Yu, Y. , Wang, X. , Lin, Y. , Yang, M. , Qiao, Y. , Wang, F. Y. (2024) The Shadow of Fraud: The Emerging Danger of AI-powered Social Engineering and its Possible Cure. arXiv preprint arXiv:2407. 15912.

[5]. Kaur, A. , Kaur, P. (2023) Predicting customers’ intentions to adopt the solar net metering system in India. International Journal of Energy Sector Management, 17(6): 1252-1270.

[6]. Sraml Gonzalez, J. , Gulbrandsen, M. (2022) Innovation in established industries undergoing digital transformation: the role of collective identity and public values. Innovation, 24(1): 201-230.

[7]. Behera, R. K. , Gunasekaran, A. , Gupta, S. , Kamboj, S. , Bala, P. K. (2020) Personalized digital marketing recommender engine. Journal of Retailing and Consumer Services, 53: 101799.

[8]. Frey, M. (2021). Netflix recommends: algorithms, film choice, and the history of taste. Univ of California Press.

[9]. Guo, B. , Jiang, Z. B. (2023) Influence of personalised advertising copy on consumer engagement: A field experiment approach. Electronic Commerce Research, 1-30.

[10]. Sahni, N. S. , Narayanan, S. , Kalyanam, K. (2019) An experimental investigation of the effects of retargeted advertising: The role of frequency and timing. Journal of Marketing Research, 56(3): 401-418.

[11]. Skillius, E. , Jacobsson, A. (2024) Beyond the Algorithm-How AI-Driven Personalized Ads Shape Consumer Loyalty.

[12]. Schwartz, B. (2015) The paradox of choice. Positive psychology in practice: Promoting human flourishing in work, health, education, and everyday life, 121-138.

[13]. Sapountzi, A. , & Psannis, K. E. (2018) Social networking data analysis tools & challenges. Future Generation Computer Systems, 86, 893-913.

[14]. ur Rehman, I. (2019) Facebook-Cambridge Analytica data harvesting: What you need to know. Library Philosophy and Practice, 1-11.

[15]. Hinds, J. , Williams, E. J. , & Joinson, A. N. (2020). “It wouldn't happen to me”: Privacy concerns and perspectives following the Cambridge Analytica scandal. International Journal of Human-Computer Studies, 143, 102498.

[16]. Mittelstadt, B. (2021) Interpretability and transparency in artificial intelligence. The Oxford Handbook of Digital Ethics (online edn, Oxford Academic, 10 Nov. 2021). https://doi. org/10. 1093/oxfordhb/9780198857815. 013, 20

[17]. Raiser, K. , Kornek, U. , Flachsland, C. , Lamb, W. F. (2020) Is the Paris Agreement effective? A systematic map of the evidence. Environmental Research Letters, 15(8): 083006.

[18]. Sharot, T. , Rollwage, M. , Sunstein, C. R. , Fleming, S. M. (2023) Why and when beliefs change. Perspectives on Psychological Science, 18(1): 142-151.

[19]. Tufekci, Z. (2014, May) Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In Proceedings of the international AAAI conference on web and social media (Vol. 8, No. 1, pp. 505-514).

[20]. Cadwalladr, C. , Graham-Harrison, E. (2018) ao Cambridge Analytica: links to Moscow oil firm and St Petersburg university. Sat, 17, 17-59.

[21]. DeNardis, L. , Hackl, A. M. (2015) Internet governance by social media platforms. Telecommunications Policy, 39(9): 761-770.

References

[1]. Pai, C. K. , Liu, Y. , Kang, S. , Dai, A. (2020) The role of perceived smart tourism technology experience for tourist satisfaction, happiness and revisit intention. Sustainability, 12(16):6592.

[2]. Donahue, M. (2021) " Times They Are a Changin"-Can the Ad Tech Industry Survive in a Privacy Conscious World?. Cath. UJL & Tech, 30: 193.

[3]. Davenport, T. , Kalakota, R. (2019) The potential for artificial intelligence in healthcare. Future healthcare journal, 6(2): 94-98.

[4]. Yu, J. , Yu, Y. , Wang, X. , Lin, Y. , Yang, M. , Qiao, Y. , Wang, F. Y. (2024) The Shadow of Fraud: The Emerging Danger of AI-powered Social Engineering and its Possible Cure. arXiv preprint arXiv:2407. 15912.

[5]. Kaur, A. , Kaur, P. (2023) Predicting customers’ intentions to adopt the solar net metering system in India. International Journal of Energy Sector Management, 17(6): 1252-1270.

[6]. Sraml Gonzalez, J. , Gulbrandsen, M. (2022) Innovation in established industries undergoing digital transformation: the role of collective identity and public values. Innovation, 24(1): 201-230.

[7]. Behera, R. K. , Gunasekaran, A. , Gupta, S. , Kamboj, S. , Bala, P. K. (2020) Personalized digital marketing recommender engine. Journal of Retailing and Consumer Services, 53: 101799.

[8]. Frey, M. (2021). Netflix recommends: algorithms, film choice, and the history of taste. Univ of California Press.

[9]. Guo, B. , Jiang, Z. B. (2023) Influence of personalised advertising copy on consumer engagement: A field experiment approach. Electronic Commerce Research, 1-30.

[10]. Sahni, N. S. , Narayanan, S. , Kalyanam, K. (2019) An experimental investigation of the effects of retargeted advertising: The role of frequency and timing. Journal of Marketing Research, 56(3): 401-418.

[11]. Skillius, E. , Jacobsson, A. (2024) Beyond the Algorithm-How AI-Driven Personalized Ads Shape Consumer Loyalty.

[12]. Schwartz, B. (2015) The paradox of choice. Positive psychology in practice: Promoting human flourishing in work, health, education, and everyday life, 121-138.

[13]. Sapountzi, A. , & Psannis, K. E. (2018) Social networking data analysis tools & challenges. Future Generation Computer Systems, 86, 893-913.

[14]. ur Rehman, I. (2019) Facebook-Cambridge Analytica data harvesting: What you need to know. Library Philosophy and Practice, 1-11.

[15]. Hinds, J. , Williams, E. J. , & Joinson, A. N. (2020). “It wouldn't happen to me”: Privacy concerns and perspectives following the Cambridge Analytica scandal. International Journal of Human-Computer Studies, 143, 102498.

[16]. Mittelstadt, B. (2021) Interpretability and transparency in artificial intelligence. The Oxford Handbook of Digital Ethics (online edn, Oxford Academic, 10 Nov. 2021). https://doi. org/10. 1093/oxfordhb/9780198857815. 013, 20

[17]. Raiser, K. , Kornek, U. , Flachsland, C. , Lamb, W. F. (2020) Is the Paris Agreement effective? A systematic map of the evidence. Environmental Research Letters, 15(8): 083006.

[18]. Sharot, T. , Rollwage, M. , Sunstein, C. R. , Fleming, S. M. (2023) Why and when beliefs change. Perspectives on Psychological Science, 18(1): 142-151.

[19]. Tufekci, Z. (2014, May) Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In Proceedings of the international AAAI conference on web and social media (Vol. 8, No. 1, pp. 505-514).

[20]. Cadwalladr, C. , Graham-Harrison, E. (2018) ao Cambridge Analytica: links to Moscow oil firm and St Petersburg university. Sat, 17, 17-59.

[21]. DeNardis, L. , Hackl, A. M. (2015) Internet governance by social media platforms. Telecommunications Policy, 39(9): 761-770.

Cite this article

Li,Y. (2025). AI-driven Personalization on Social Media: Enhancing User Experience or Invasion of Privacy. Lecture Notes in Education Psychology and Public Media,108,34-39.

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 the 2nd International Conference on Global Politics and Socio-Humanities

ISBN: 978-1-80590-277-5(Print) / 978-1-80590-278-2(Online)
Editor: Enrique Mallen
Conference website: https://2024.icgpsh.org/
Conference date: 20 December 2024
Series: Lecture Notes in Education Psychology and Public Media
Volume number: Vol.108
ISSN: 2753-7048(Print) / 2753-7056(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:

1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).

For authors
For editors
For reviewers

Cookies are used by this site.
Copyright © 2024 EWA Publishing, its licensors, and contributors. All rights reserved, including text and data mining, AI training, and similar technologies.