Second, our work highlights the poten-tial of LLMs for synthetic dataset generation, a critical area in network science. Although the accuracy ofLLM-based predictions is not yet perfect, like all other link prediction models, this approach is particu-larly valuable in scenarios where privacy concerns limit access to real-world data. By simulating realisticdatasets that capture important network properties, LLMs can facilitate research and experimentationwithout compromising sensitive informatio
Valuable where privacy concerns limit access to real-world data (synthetic dataset generation).
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