Curated papers, datasets, and benchmarks for social network simulation, from classical network models to LLM-based agentic social systems. The repository is authored by tamlhp and was last updated on 2026-05-07 11:53:09.
Use Cases
- Benchmarking new social network models against established classical models.
- Training LLM-based agents for social simulation using curated datasets.
- Studying the evolution of agentic social systems based on provided papers and benchmarks.
Strengths
- Repository is licensed under Apache-2.0, allowing for commercial use and modification.
- The description indicates curation across multiple resource types: papers, datasets, and benchmarks.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
Provenance
- Source
- github
- Collection Method
- Curated collection by author tamlhp.
- Freshness
- Last updated 2026-05-07 11:53:09; freshness should be verified.