# Modeling Social Organizations as Communication Networks

**Authors:** David Wolpert, Justin Grana, Brendan Tracey, Tim Kohler and, Artemy Kolchinsky

arXiv: 1702.04449 · 2017-02-16

## TL;DR

This paper models human social organizations as communication networks and introduces three theoretical approaches—network coding, resource allocation, and neural networks—to analyze their structure based on information processing and welfare optimization.

## Contribution

It presents three novel theoretical frameworks for understanding social organization structures using communication network analysis and optimization techniques.

## Key findings

- Network coding improves information conveyance in organizations.
- Linear programming models resource allocation under environmental uncertainty.
- Neural networks facilitate information synthesis and transformation.

## Abstract

We identify the "organization" of a human social group as the communication network(s) within that group. We then introduce three theoretical approaches to analyzing what determines the structures of human organizations. All three approaches adopt a group-selection perspective, so that the group's network structure is (approximately) optimal, given the information-processing limitations of agents within the social group, and the exogenous welfare function of the overall group. In the first approach we use a new sub-field of telecommunications theory called network coding, and focus on a welfare function that involves the ability of the organization to convey information among the agents. In the second approach we focus on a scenario where agents within the organization must allocate their future communication resources when the state of the future environment is uncertain. We show how this formulation can be solved with a linear program. In the third approach, we introduce an information synthesis problem in which agents within an organization receive information from various sources and must decide how to transform such information and transmit the results to other agents in the organization. We propose leveraging the computational power of neural networks to solve such problems. These three approaches formalize and synthesize work in fields including anthropology, archeology, economics and psychology that deal with organization structure, theory of the firm, span of control and cognitive limits on communication.

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/1702.04449/full.md

## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/1702.04449/full.md

## References

36 references — full list in the complete paper: https://tomesphere.com/paper/1702.04449/full.md

---
Source: https://tomesphere.com/paper/1702.04449