OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Auditing YouTube’s Recommendation Algorithm for Misinformation Filter Bubbles
Ivan Srba, Róbert Móro, Matúš Tomlein, et al.
ACM Transactions on Recommender Systems (2022) Vol. 1, Iss. 1, pp. 1-33
Open Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Engagement, user satisfaction, and the amplification of divisive content on social media
Smitha Milli, Micah Carroll, Yike Wang, et al.
PNAS Nexus (2025) Vol. 4, Iss. 3
Open Access | Times Cited: 1

Investigation of the Misinformation about COVID-19 on YouTube Using Topic Modeling, Sentiment Analysis, and Language Analysis
Nirmalya Thakur, Shuqi Cui, Victoria Knieling, et al.
Computation (2024) Vol. 12, Iss. 2, pp. 28-28
Open Access | Times Cited: 6

Human-AI Coevolution
Dino Pedreschi, Luca Pappalardo, Emanuele Ferragina, et al.
Artificial Intelligence (2024) Vol. 339, pp. 104244-104244
Open Access | Times Cited: 4

Personalization, Echo Chambers, News Literacy, and Algorithmic Literacy: A Qualitative Study of AI-Powered News App Users
Ying Du
Journal of Broadcasting & Electronic Media (2023) Vol. 67, Iss. 3, pp. 246-273
Closed Access | Times Cited: 10

Understanding the influence of data characteristics on the performance of point-of-interest recommendation algorithms
Linus W. Dietz, Pablo Sánchez, Alejandro Bellogín
Information Technology & Tourism (2025)
Open Access

When Anti-Fraud Laws Become a Barrier to Computer Science Research
Madelyne Xiao, Andrew Sellars, Sarah Scheffler
(2025), pp. 1-16
Closed Access

Disinformation tackling in the metaverse and the Digital Services Act
Tanel Kerikmäe, Ondrej Hamuľák, Matúš Mesarčík
Cogent Social Sciences (2025) Vol. 11, Iss. 1
Open Access

A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes
David Hartmann, Sonja Mei Wang, Lena Pohlmann, et al.
Journal of Computational Social Science (2025) Vol. 8, Iss. 2
Open Access

The bias beneath: analyzing drift in YouTube’s algorithmic recommendations
Mert Can Çakmak, Nitin Agarwal, Remi Oni
Social Network Analysis and Mining (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2

Unveiling Bias in YouTube Shorts: Analyzing Thumbnail Recommendations and Topic Dynamics
Mert Can Çakmak, Nitin Agarwal, S. Dağtaş, et al.
Lecture notes in computer science (2024), pp. 205-215
Closed Access | Times Cited: 2

Unbiased, Effective, and Efficient Distillation from Heterogeneous Models for Recommender Systems
SeongKu Kang, Wonbin Kweon, Dongha Lee, et al.
ACM Transactions on Recommender Systems (2024)
Open Access | Times Cited: 1

Link Prediction Based on Feature Mapping and Bi-Directional Convolution
Ping Feng, Xin Zhang, Hang Wu, et al.
Applied Sciences (2024) Vol. 14, Iss. 5, pp. 2089-2089
Open Access | Times Cited: 1

YouTube and Conspiracy Theories: A Longitudinal Audit of Information Panels
Lillie Godinez, Eni Mustafaraj
(2024), pp. 273-284
Closed Access | Times Cited: 1

“The algorithm is like a mercurial god”: Exploring content creators’ perception of algorithmic agency on YouTube
Roland Verwiebe, Claudia Buder, S. Weissmann, et al.
New Media & Society (2024)
Closed Access | Times Cited: 1

Cyclops: Looking beyond the single perspective in information access systems
Anthi Ioannou, Nicolas Ioannou, Styliani Kleanthous
(2023), pp. 34-37
Closed Access | Times Cited: 2

Reducing Exposure to Harmful Content via Graph Rewiring
Corinna Coupette, Stefan Neumann, Aristides Gionis
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2023), pp. 323-334
Open Access | Times Cited: 2

8–10% of algorithmic recommendations are ‘bad’, but… an exploratory risk-utility meta-analysis and its regulatory implications
Martin Hilbert, Arti Thakur, Pablo M. Flores, et al.
International Journal of Information Management (2023) Vol. 75, pp. 102743-102743
Open Access | Times Cited: 1

Evaluating Bias and Fairness in AI: An Analysis of YouTube’s Recommendation Algorithm and its Impact on Geopolitical Discourse
Mert Can Çakmak, Nitin Agarwal, Obianuju Okeke, et al.
Research Square (Research Square) (2024)
Open Access

“I Searched for a Religious Song in Amharic and Got Sexual Content Instead’’: Investigating Online Harm in Low-Resourced Languages on YouTube.
Hellina Hailu Nigatu, Inioluwa Deborah Raji
2022 ACM Conference on Fairness, Accountability, and Transparency (2024), pp. 141-160
Open Access

How Does Empowering Users with Greater System Control Affect News Filter Bubbles?
Ping Liu, Karthik Shivaram, Aron Culotta, et al.
Proceedings of the International AAAI Conference on Web and Social Media (2024) Vol. 18, pp. 943-957
Open Access

Risk Governance and Optimization of the Intelligent News Algorithm Recommendation Mechanism
Yijin Lu, Xiaomei Li, Lei Wu
International Journal of Modern Physics C (2024)
Closed Access

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