# Inferring Personal Economic Status from Social Network Location

## TL;DR

This paper demonstrates that an individual's position within social networks, measured by collective influence, can accurately predict personal economic status and improve targeted marketing efforts.

## Contribution

It introduces a network-based measure of influence that correlates with economic wellbeing and validates its practical utility through marketing and policy applications.

## Key findings

- High correlation between social influence and economic status
- Three-fold increase in marketing response rate using network-based targeting
- Potential to enhance economic stimulus effectiveness

## Abstract

It is commonly believed that patterns of social ties affect individuals' economic status. Here, we translate this concept into an operational definition at the network level, which allows us to infer the economic wellbeing of individuals through a measure of their location and influence in the social network. We analyze two large-scale sources: telecommunications and financial data of a whole country's population. Our results show that an individual's location, measured as the optimal collective influence to the structural integrity of the social network, is highly correlated with personal economic status. The observed social network patterns of influence mimics the patterns of economic inequality. For pragmatic use and validation, we carry out a marketing campaign that shows a three-fold increase in response rate by targeting individuals identified by our social network metrics as compared to random targeting. Our strategy can also be useful in maximizing the effects of large-scale economic stimulus policies.