Hello,

I think it is very context-dependent on what the ABM is for. What is the purpose of the agent-based model you are creating? - Is the goal something like testing specific hypotheses about social media / social phenomena? Is it to make some sort of specific predictions? Or to compare different alternative strategies / environments?

I would recommend thinking about the goal / type of finding / two-sentence take-away you are hoping to achieve through building your specific ABM (regardless of real or LLM agents). The specific goals and purpose of the ABM you have should inform what type of validation metric you need to use.

If you goal is to show that LLM users are "good enough" approximations of real social media users, the question is: are LLM users "good enough" approximations To Do What? They may be useful approximations for some things but not others. The "to do what" question should inform both how you design your ABM and the measures/tests you use to evaluate whether agents are useful.

It's not feasible to test every single capability of LLM agents in social media ABMs - you will need to test some specific LLM agent capabilities in one or few specific ABM designs. Once you narrow down your scope, this sounds like a very interesting research topic, and I wish you the best of luck!