The field of large language models (LLMs) is rapidly advancing, with a growing focus on their application in social simulations and online discourse. Recent studies have investigated the ability of LLMs to mimic human interactions, generate realistic comments, and influence political debate. The use of LLMs in social simulations has raised concerns about their potential to manipulate public opinion and shape political narratives. Researchers are working to develop more rigorous methods for evaluating the empirical realism of LLMs and ensuring that they are used in a transparent and explainable manner. Noteworthy papers in this area include:
- A study on the Public Service Algorithm, which introduces a novel framework for scalable and transparent content curation based on public service media values.
- A paper on Generative Exaggeration in LLM Social Agents, which investigates how LLMs behave when simulating political discourse on social media and finds that they can amplify polarization and introduce structural biases.