# The Mobility Network of Scientists: Analyzing Temporal Correlations in Scientific Careers

## TL;DR

This study analyzes the career mobility of scientists using higher-order network methods on 3.5 million trajectories, revealing strong temporal correlations at university and country levels, but not at city level, informing institutional mobility policies.

## Contribution

Introduces a novel higher-order network approach to quantify temporal correlations in scientists' career trajectories across multiple geographic levels.

## Key findings

- Strong temporal correlations at top universities and countries.
- No significant correlations found at city level.
- Insights into institutional path dependence and mobility program effectiveness.

## Abstract

The mobility of scientists between different universities and countries is important to foster knowledge exchange. At the same time, the potential mobility is restricted by geographic and institutional constraints, which leads to temporal correlations in the career trajectories of scientists. To quantify this effect, we extract 3.5 million career trajectories of scientists from two large scale bibliographic data sets and analyze them applying a novel method of higher-order networks. We study the effect of temporal correlations at three different levels of aggregation, universities, cities and countries. We find strong evidence for such correlations for the top 100 universities, i.e. scientists move likely between specific institutions. These correlations also exist at the level of countries, but cannot be found for cities. Our results allow to draw conclusions about the institutional path dependence of scientific careers and the efficiency of mobility programs.