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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:

Synthetic Replacements for Human Survey Data? The Perils of Large Language Models
James Bisbee, Joshua D. Clinton, Cassy Dorff, et al.
(2023)
Open Access | Times Cited: 17

Showing 17 citing articles:

Artificial Intelligence and Democracy: A Conceptual Framework
Andreas Jungherr
Social Media + Society (2023) Vol. 9, Iss. 3
Open Access | Times Cited: 54
GPT is an effective tool for multilingual psychological text analysis
Steve Rathje, Dan-Mircea Mirea, Ilia Sucholutsky, et al.
Proceedings of the National Academy of Sciences (2024) Vol. 121, Iss. 34
Open Access | Times Cited: 48
Can Generative AI improve social science?
Christopher A. Bail
Proceedings of the National Academy of Sciences (2024) Vol. 121, Iss. 21
Open Access | Times Cited: 47
Large language models as a substitute for human experts in annotating political text
Michael Heseltine, Bernhard Clemm von Hohenberg
Research & Politics (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 14
Donald Trumps in the Virtual Polls: Simulating and Predicting Public Opinions in Surveys Using Large Language Models
Chen Zhang, Lijia Wei, Song Jiang
(2025)
Open Access
Comments on “AI and the advent of the cyborg behavioral scientist”
Paul Andrew Blythe, Christopher Kulis, A. Peter McGraw, et al.
Journal of Consumer Psychology (2025)
Closed Access
What does AI consider praiseworthy?
Andrew Jerel Peterson
AI and Ethics (2025)
Closed Access
Demonstrations of the Potential of AI-based Political Issue Polling
Nathan Sanders, Alex Ulinich, Bruce Schneier
Harvard data science review (2023) Vol. 5, Iss. 4
Open Access | Times Cited: 10
Science in the era of ChatGPT, large language models and generative AI
Evangelos Pournaras
transcript Verlag eBooks (2023), pp. 275-290
Open Access | Times Cited: 2
Assessing Bias in LLM-Generated Synthetic Datasets: The Case of German Voter Behavior
Leah von der Heyde, Anna‐Carolina Haensch, Alexander Wenz
(2023)
Open Access | Times Cited: 2
Vox Populi, Vox AI? Using Language Models to Estimate German Public Opinion
Leah von der Heyde, Anna‐Carolina Haensch, Alexander Wenz
(2023)
Open Access | Times Cited: 2
The Mixed Subjects Design: Treating Large Language Models as (Potentially) Informative Observations
David Broska, Michael Howes, Austin van Loon
(2024)
Open Access
Chrono-Sampling: Generative AI Enabled Time Machine for Public Opinion Data Collection
Eduardo Ryô Tamaki, Levente Littvay
(2024)
Open Access
Towards More Accurate US Presidential Election via Multi-step Reasoning with Large Language Models
Chenxiao Yu, Zhaotian Weng, Zheng Li, et al.
(2024)
Closed Access
Concept-Guided Chain-of-Thought Prompting for Pairwise Comparison Scoring of Texts with Large Language Models
Patrick Y. Wu, Jonathan Nagler, Joshua A. Tucker, et al.
2021 IEEE International Conference on Big Data (Big Data) (2024), pp. 7232-7241
Closed Access
Beyond Quantity

transcript Verlag eBooks (2023)
Open Access
Beyond Quantity

AI critique (2023)
Open Access
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