Reinforced communication and social navigation: remember your friends and remember yourself

TL;DR

This paper introduces an agent-based model to explore how social networks and ideas co-evolve, emphasizing the importance of historical interactions in understanding information flow and network dynamics.

Contribution

It presents a novel simple model that captures the feedback between social network structure and ideas, highlighting the role of past events in social dynamics.

Findings

Ideas are easier to recover from network structure than the other way around.

Historical interactions significantly influence the coupling between ideas and social networks.

Abstract

In social systems, people communicate with each other and form groups based on their interests. The pattern of interactions, the network, and the ideas that flow on the network naturally evolve together. Researchers use simple models to capture the feedback between changing network patterns and ideas on the network, but little is understood about the role of past events in the feedback process. Here we introduce a simple agent-based model to study the coupling between peoples' ideas and social networks, and better understand the role of history in dynamic social networks. We measure how information about ideas can be recovered from information about network structure and, the other way around, how information about network structure can be recovered from information about ideas. We find that it is in general easier to recover ideas from the network structure than vice versa.