# Implication Avoiding Dynamics for Externally Observed Networks

## TL;DR

This paper introduces a model where agents modify their network connections to appear credible externally, analyzing strategies for identifying credible nodes and proposing dynamics that explain group fracture due to external perception concerns.

## Contribution

It presents a new model of external-appearance-driven network dynamics and analyzes the ability of observers to identify credible nodes, including a heuristic and a dynamical system for implication avoiding.

## Key findings

- External observers can identify honest nodes despite adversarial connections.
- Some identification problems are NP-hard, indicating computational difficulty.
- Implication avoiding dynamics can explain group fracture phenomena.

## Abstract

Previous network models have imagined that connections change to promote structural balance, or to reflect hierarchies. We propose a model where agents adjust their connections to appear credible to an external observer. In particular, we envision a signed, directed network where positive edges represent endorsements or trust and negative edges represent accusations or doubt, and consider both the strategies an external observer might use to identify credible nodes and the strategies nodes might use to then appear credible by changing their outgoing edges. First, we establish that an external observer may be able to exactly identify a set of 'honest' nodes from an adversarial set of 'cheater' nodes regardless of the 'cheater' nodes' connections. However, while these results show that an external observer's task is not hopeless, some of these theorems involve network structures that are NP-hard to find. Instead, we suggest a simple heuristic that an external observer might use to identify which nodes are not credible based upon their involvement with particular implicating edge motifs. Building on these notions, and analogously to some models of structural balance, we develop a discrete time dynamical system where nodes engage in implication avoiding dynamics, where inconsistent arrangements of edges that cause a node to look 'suspicious' exert pressure for that node to change edges. We demonstrate that these dynamics provide a new way to understand group fracture when nodes are worried about appearing consistent to an external observer.