The diplomat's dilemma: Maximal power for minimal effort in social networks

TL;DR

This paper explores how social agents in networks balance the desire for central influence with the need to keep social ties minimal, using an adaptive model where agents optimize their positions based on local information.

Contribution

It introduces a novel adaptive network model where agents strategically optimize their centrality while minimizing social ties, reflecting real-world social costs.

Findings

Agents develop strategies balancing centrality and social tie costs.

Network evolution shows emergence of efficient influence strategies.

Local information suffices for agents to optimize their positions.

Abstract

Closeness is a global measure of centrality in networks, and a proxy for how influential actors are in social networks. In most network models, and many empirical networks, closeness is strongly correlated with degree. However, in social networks there is a cost of maintaining social ties. This leads to a situation (that can occur in the professional social networks of executives, lobbyists, diplomats and so on) where agents have the conflicting objectives of aiming for centrality while simultaneously keeping the degree low. We investigate this situation in an adaptive network-evolution model where agents optimize their positions in the network following individual strategies, and using only local information. The strategies are also optimized, based on the success of the agent and its neighbors. We measure and describe the time evolution of the network and the agents' strategies.