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Found 8 papers, 2 papers with code
Using Language Models to Decipher the Motivation Behind Human Behaviors
By varying prompts to a large language model, we can elicit the full range of human behaviors in a variety of different scenarios in classic economic games.
How Different AI Chatbots Behave? Benchmarking Large Language Models in Behavioral Economics Games
The deployment of large language models (LLMs) in diverse applications requires a thorough understanding of their decision-making strategies and behavioral patterns.
Multiplexing in Networks and Diffusion
Second, we examine how these layers and their overlap affect information diffusion in a field experiment.
A Turing Test: Are AI Chatbots Behaviorally Similar to Humans?
Their behaviors are often distinct from average and modal human behaviors, in which case they tend to behave on the more altruistic and cooperative end of the distribution.
Games Under Network Uncertainty
We develop a model in which agents use local knowledge of their direct (and in some cases indirect) connections to make inferences about the complementarity strength of their actions with other agents in the society.
Systemic Risk in Financial Networks: A Survey
We provide an overview of the relationship between financial networks and systemic risk.
Pricing and Referrals in Diffusion on Networks
When a new product or technology is introduced, potential consumers can learn its quality by trying the product, at a risk, or by letting others try it and free-riding on the information that they generate.
Economics Computer Science and Game Theory Social and Information Networks Physics and Society 91D30, 05C82, 91A43
Tractable and Consistent Random Graph Models
We define a general class of network formation models, Statistical Exponential Random Graph Models (SERGMs), that nest standard exponential random graph models (ERGMs) as a special case.
Physics and Society Social and Information Networks
