Collective Intelligence in Dynamic Networks

• Tác giả: Florian Mudekereza
• Ngôn ngữ: eng
• Ký hiệu phân loại: 327.1201 Foreign policy and specific topics in international relations
• Thông tin xuất bản: 2025
• Bộ sưu tập: Metadata
• ID: 223756

Tóm tắt

We revisit DeGroot learning to examine the robustness of social learning outcomes in dynamic networks -- networks that evolve randomly over time. Randomness stems from multiple sources such as random matching and strategic network formation. Our main contribution is that random dynamics have double-edged effects depending on social structure: while they can foster consensus and boost collective intelligence, they can have adverse effects such as slowing down the speed of learning and causing long-term disagreement. Collective intelligence in dynamic networks requires balancing people's average influence with their average trust as society grows. We also find that the initial social structure of a dynamic network plays a central role in shaping long-term beliefs.