The Emergence of Shared Norms in Decentralized Networks: A Social Computing Model of Lexical Coordination

The formation of shared norms, such as common terminologies or hashtags, is fundamental to collective action in online communities and decentralized systems. However, how these conventions emerge remains a complex interplay between the economic rationality of individual agents and the structural properties of their underlying social network. This paper proposes a game-theoretic multi-agent model, the ’Semantic Coordination Game,’ to investigate this process. We simulate agents negotiating a shared lexicon under communication cost constraints across three canonical network topologies: Erdős-Rényi (random), Barabási-Albert (scale-free), and Watts-Strogatz (small-world). Our simulations reveal a fundamental trade-off between communication efficiency and the expressive power of the emergent lexicon. More critically, we demonstrate that network structure dictates the distribution of norm-setting power; scale-free networks significantly amplify influence concentration, allowing a few central agents to act as de facto ’standard setters.’ This work provides a formal model that bridges semantic negotiation with computational social science, offering insights into how social structure shapes the emergence of collective understanding.