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https://doi.org/10.31235/osf.io/rwtzs
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1016/j.socnet.2008.07.002openalex-snapshot
Tastes, ties, and time: A new social network dataset using Facebook.com
inferredcites →https://doi.org/10.1016/j.tics.2023.04.008openalex-snapshot
Can AI language models replace human participants?
inferredcites →https://doi.org/10.1017/pan.2023.2openalex-snapshot
Out of One, Many: Using Language Models to Simulate Human Samples
inferredcites →https://doi.org/10.1038/d41586-023-01295-4openalex-snapshot
Why open-source generative AI models are an ethical way forward for science
inferredcites →https://doi.org/10.1038/s41586-019-0941-9openalex-snapshot
Large teams develop and small teams disrupt science and technology
inferredcites →https://doi.org/10.1038/s41586-019-1724-zopenalex-snapshot
Grandmaster level in StarCraft II using multi-agent reinforcement learning
inferredcites →https://doi.org/10.1073/pnas.1320040111openalex-snapshot
Experimental evidence of massive-scale emotional contagion through social networks
inferredcites →https://doi.org/10.1073/pnas.1613580114openalex-snapshot
Disparate foundations of scientists’ policy positions on contentious biomedical research
inferredcites →https://doi.org/10.1073/pnas.1817195116openalex-snapshot
The wisdom of partisan crowds
inferredcites →https://doi.org/10.1073/pnas.2208839120openalex-snapshot
Human heuristics for AI-generated language are flawed
inferredcites →https://doi.org/10.1073/pnas.2213709120openalex-snapshot
Using the Veil of Ignorance to align AI systems with principles of justice
inferredcites →https://doi.org/10.1073/pnas.2218523120openalex-snapshot
Using cognitive psychology to understand GPT-3
inferredcites →https://doi.org/10.1073/pnas.2305016120openalex-snapshot
ChatGPT outperforms crowd workers for text-annotation tasks
inferredcites →https://doi.org/10.1093/qje/qjx032openalex-snapshot
Human Decisions and Machine Predictions
inferredcites →https://doi.org/10.1111/rssa.12375openalex-snapshot
Bit by Bit: Social Research in the Digital Age
inferredcites →https://doi.org/10.1126/science.1240474openalex-snapshot
Atypical Combinations and Scientific Impact
inferredcites →https://doi.org/10.1126/science.aax2342openalex-snapshot
Dissecting racial bias in an algorithm used to manage the health of populations
inferredcites →https://doi.org/10.1126/science.aaz8170openalex-snapshot
Computational social science: Obstacles and opportunities
inferredcites →https://doi.org/10.1145/3442188.3445922openalex-snapshot
On the Dangers of Stochastic Parrots
inferredcites →https://doi.org/10.1145/3544548.3581318openalex-snapshot
Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions
inferredcites →https://doi.org/10.1145/3586183.3606763openalex-snapshot
Generative Agents: Interactive Simulacra of Human Behavior
inferredcites →https://doi.org/10.1146/annurev-soc-121919-054621openalex-snapshot
Computational Social Science and Sociology
inferredcites →https://doi.org/10.1146/annurev.soc.28.110601.141117openalex-snapshot
From Factors to Actors: Computational Sociology and Agent-Based Modeling
inferredcites →https://doi.org/10.1162/coli_a_00502openalex-snapshot
Can Large Language Models Transform Computational Social Science?
inferredcites →https://doi.org/10.1177/14614448231160526openalex-snapshot
The potential impact of emerging technologies on democratic representation: Evidence from a field experiment
inferredcites →https://doi.org/10.1177/2056305118763366openalex-snapshot
“Participant” Perceptions of Twitter Research Ethics
inferredcites →https://doi.org/10.18653/v1/2020.acl-main.164openalex-snapshot
Automatic Detection of Generated Text is Easiest when Humans are Fooled
inferredcites →https://doi.org/10.18653/v1/w19-3824openalex-snapshot
On Measuring Gender Bias in Translation of Gender-neutral Pronouns
inferredcites →https://doi.org/10.2139/ssrn.4310154openalex-snapshot
Does GPT-3 know what the Most Important Issue is? Using Large Language Models to Code Open-Text Social Survey Responses At Scale
inferredcites →https://doi.org/10.3386/w30957openalex-snapshot
Language Models and Cognitive Automation for Economic Research
inferredcites →https://doi.org/10.3386/w31122openalex-snapshot
Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?
inferredcites →https://doi.org/10.48550/arxiv.1410.1211openalex-snapshot
Encore: Lightweight Measurement of Web Censorship with Cross-Origin Requests
inferredcites →https://doi.org/10.48550/arxiv.2108.07258openalex-snapshot
On the Opportunities and Risks of Foundation Models
inferredcites →https://doi.org/10.48550/arxiv.2206.04615openalex-snapshot
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
inferredcites →https://doi.org/10.48550/arxiv.2208.10264openalex-snapshot
Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies
inferredcites →https://doi.org/10.48550/arxiv.2301.07543openalex-snapshot
Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?
inferredcites →https://doi.org/10.48550/arxiv.2301.10226openalex-snapshot
A Watermark for Large Language Models
inferredcites →https://doi.org/10.48550/arxiv.2302.07268openalex-snapshot
AI Chat Assistants can Improve Conversations about Divisive Topics
inferredcites →https://doi.org/10.48550/arxiv.2303.06074openalex-snapshot
Susceptibility to Influence of Large Language Models
inferredcites →https://doi.org/10.48550/arxiv.2303.12057openalex-snapshot
Large Language Models Can Be Used to Estimate the Latent Positions of Politicians
inferredcites →https://doi.org/10.48550/arxiv.2303.16779openalex-snapshot
Language Models Trained on Media Diets Can Predict Public Opinion
inferredcites →https://doi.org/10.48550/arxiv.2303.17548openalex-snapshot
Whose Opinions Do Language Models Reflect?
inferredcites →https://doi.org/10.5281/zenodo.7236700openalex-snapshot
Human-Level Play in the Game of Diplomacy by Combining Language Models with Strategic Reasoning
inferredcites →https://doi.org/10.5860/choice.31-0574openalex-snapshot
Agendas and instability in American politics
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4872205openalex-extracted
Navigating the Sea of Reviews: Unveiling the Effects of Introducing AI-Generated Summaries in E-Commerce
inferred← citeshttps://doi.org/10.2139/ssrn.5060022openalex-extracted
AI-Powered (Finance) Scholarship
inferred← citeshttps://doi.org/10.2139/ssrn.5213130openalex-extracted
Behavioral Economics of AI: LLM Biases and Corrections
inferred← citeshttps://doi.org/10.2139/ssrn.5389144openalex-extracted
Predicting Field Experiments with Large Language Models
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Multi‐Agent‐Network‐Based Idea Generator for Zinc‐Ion Battery Electrolyte Discovery: A Case Study on Zinc Tetrafluoroborate Hydrate‐Based Deep Eutectic Electrolytes
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ChatGPT in Product Management
inferred← citeshttps://doi.org/10.1007/978-3-031-62362-2_3openalex-snapshot
Inclusive Counterfactual Generation: Leveraging LLMs in Identifying Online Hate
inferred← citeshttps://doi.org/10.1007/978-3-032-19684-2_37openalex-snapshot
Societal Risks of Generative AI: A Comparative Analysis
inferred← citeshttps://doi.org/10.1007/s00146-024-01889-0openalex-snapshot
Generative AI and human–robot interaction: implications and future agenda for business, society and ethics
inferred← citeshttps://doi.org/10.1007/s11135-023-01753-1openalex-snapshot
Comparing qualitative and quantitative text analysis methods in combination with document-based social network analysis to understand policy networks
inferred← citeshttps://doi.org/10.1007/s11704-024-40231-1openalex-snapshot
A survey on large language model based autonomous agents
inferred← citeshttps://doi.org/10.1016/j.aej.2024.12.079openalex-snapshot
Generative artificial intelligence in construction: A Delphi approach, framework, and case study
inferred← citeshttps://doi.org/10.1016/j.cities.2025.106334openalex-snapshot
Artificial intelligence for spatial analysis in cities
inferred← citeshttps://doi.org/10.1016/j.indmarman.2023.09.012openalex-snapshot
Social media analytics for business-to-business marketing
inferred← citeshttps://doi.org/10.1016/j.techsoc.2025.102836openalex-snapshot
The ethics of generative AI in social science research: A qualitative approach for institutionally grounded AI research ethics
inferred← citeshttps://doi.org/10.1038/s41598-025-93794-9openalex-snapshot
Generative AI lacks the human creativity to achieve scientific discovery from scratch
inferred← citeshttps://doi.org/10.1038/s42256-023-00783-6openalex-snapshot
The dangers of using proprietary LLMs for research
inferred← citeshttps://doi.org/10.1038/s44168-026-00375-1openalex-snapshot
On using large language models to support social research for climate action
inferred← citeshttps://doi.org/10.1080/10447318.2023.2295725openalex-snapshot
Exploring the Early Adoption of Open AI among Laypeople and Technical Professionals: An Analysis of Twitter Conversations on #ChatGPT and #GPT3
inferred← citeshttps://doi.org/10.1080/17516234.2024.2370716openalex-snapshot
Situated usage of generative AI in policy education: implications for teaching, learning, and research
inferred← citeshttps://doi.org/10.1093/oxfordhb/9780197653609.013.39openalex-snapshot
Machine Learning and the Analysis of Culture
inferred← citeshttps://doi.org/10.1145/3584931.3606955openalex-snapshot
Shaping the Emerging Norms of Using Large Language Models in Social Computing Research
inferred← citeshttps://doi.org/10.1145/3706598.3713120openalex-snapshot
Large Language Models in Qualitative Research: Uses, Tensions, and Intentions
inferred← citeshttps://doi.org/10.1162/coli_a_00502openalex-snapshot
Can Large Language Models Transform Computational Social Science?
inferred← citeshttps://doi.org/10.1177/00491241251337316openalex-snapshot
Simulating Subjects: The Promise and Peril of Artificial Intelligence Stand-Ins for Social Agents and Interactions
inferred← citeshttps://doi.org/10.1177/08944393251370354openalex-snapshot
Dialogues Towards Sociologies of Generative AI
inferred← citeshttps://doi.org/10.1177/16094069251322346openalex-snapshot
“Conversing” With Qualitative Data: Enhancing Qualitative Research Through Large Language Models (LLMs)
inferred← citeshttps://doi.org/10.1177/20539517241303126openalex-snapshot
Synthetic ethnography: Field devices for the qualitative study of generative models
inferred← citeshttps://doi.org/10.1177/23780231241261596openalex-snapshot
Artificial Intelligence Policymaking: An Agenda for Sociological Research
inferred← citeshttps://doi.org/10.1177/27538699231206210openalex-snapshot
Large language models in the labyrinth: Possibility spaces and moral constraints
inferred← citeshttps://doi.org/10.1186/s40309-024-00238-0openalex-snapshot
CERN for AI: a theoretical framework for autonomous simulation-based artificial intelligence testing and alignment
inferred← citeshttps://doi.org/10.1371/journal.pone.0320094openalex-snapshot
Static network structure cannot stabilize cooperation among large language model agents
inferred← citeshttps://doi.org/10.1371/journal.pone.0330217openalex-snapshot
Frankenstein, thematic analysis and generative artificial intelligence: Quality appraisal methods and considerations for qualitative research
inferred← citeshttps://doi.org/10.1515/pdtc-2024-0086openalex-snapshot
Using Digital Technologies for Indigenous Sociocultural Advancement in an Era of AI: A Systematic Critical Synthesis
inferred← citeshttps://doi.org/10.2139/ssrn.4961494openalex-snapshot
LLM-Measure: Generating Valid, Consistent, and Reproducible Text-Based Measures for Social Science Research
inferred← citeshttps://doi.org/10.2139/ssrn.5053570openalex-snapshot
Agent-Enhanced Large Language Models for Researching Political Institutions
inferred← citeshttps://doi.org/10.2139/ssrn.5170182openalex-snapshot
Beyond Stochastic Parroting: LLMs' Human-Like Behavioral Biases Emerge from Linear Neural Representations
inferred← citeshttps://doi.org/10.2139/ssrn.5274559openalex-snapshot
Be.FM: Open Foundation Models for Human Behavior
inferred← citeshttps://doi.org/10.2139/ssrn.5357062openalex-snapshot
Rethinking the Role of Crowds in the Age of AI
inferred← citeshttps://doi.org/10.2139/ssrn.5381862openalex-snapshot
Revisiting the Spiral of Silence: A Personality- and Issue-Based Simulation
inferred← citeshttps://doi.org/10.21825/snm.95476openalex-snapshot
Computational Methods and Nationalism Studies
inferred← citeshttps://doi.org/10.22541/essoar.171136837.71755629/v1openalex-snapshot
Potential Benefits and Dangers of Using Large Language Models for Advancing Sustainability Science and Communication
inferred← citeshttps://doi.org/10.31234/osf.io/q6x23openalex-snapshot
Americans’ attitudes toward advancements in generative artificial intelligence
inferred← citeshttps://doi.org/10.31234/osf.io/zvk7bopenalex-snapshot
Large Language Models in the Labyrinth: Possibility Spaces and Moral Constraints
inferred← citeshttps://doi.org/10.31235/osf.io/6jq32openalex-snapshot
Generative Multimodal Models for Social Science: An Application with Satellite and Streetscape Imagery
inferred← citeshttps://doi.org/10.31235/osf.io/j3bntopenalex-snapshot
The Mixed Subjects Design: Treating Large Language Models as Potentially Informative Observations
inferred← citeshttps://doi.org/10.31235/osf.io/r2pnbopenalex-snapshot
How do Generative Language Models Answer Opinion Polls?
inferred← citeshttps://doi.org/10.31235/osf.io/wg82kopenalex-snapshot
Updating “The Future of Coding”: Qualitative Coding with Generative Large Language Models
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ChatGPT for Text Annotation? Mind the Hype!
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“Conversing” with Qualitative Data: Enhancing Qualitative Research through Large Language Models (LLMs)
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AI and Data Science for Public Policy
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A step-by-step method for cultural annotation by LLMs
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Media, media education, GAI and radical uncertainty
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Revolutionizing Program Evaluation with Generative AI: An Evidence-Based Methodology
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The Role of Habit in Promoting Generative AI Adoption Among Social Science Students and Researchers
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An Ethical Study of Generative AI from the Actor-Network Theory Perspective
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Generative AI for Business Analytics: Decision-Making, Model Governance, and Performance Measurement
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Development of Economics Teaching Materials Using Android-Based Mit App Software
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