Social stratification in networks: insights from co-authorship networks.

Zeinab S Jalali, Josh Introne, Sucheta Soundarajan
Author Information
  1. Zeinab S Jalali: Electrical Engineering and Computer Science, Syracuse University, NY, Syracuse, USA. ORCID
  2. Josh Introne: School of Information Studies, Syracuse University, NY, Syracuse, USA.
  3. Sucheta Soundarajan: Electrical Engineering and Computer Science, Syracuse University, NY, Syracuse, USA.

Abstract

It has been observed that real-world social networks often exhibit stratification along economic or other lines, with consequences for class mobility and access to opportunities. With the rise in human interaction data and extensive use of online social networks, the structure of social networks (representing connections between individuals) can be used for measuring stratification. However, although stratification has been studied extensively in the social sciences, there is no single, generally applicable metric for measuring the level of stratification in a network. In this work, we first propose the novel Stratification Assortativity (StA) metric, which measures the extent to which a network is stratified into different tiers. Then, we use the StA metric to perform an in-depth analysis of the stratification of five co-authorship networks. We examine the evolution of these networks over 50 years and show that these fields demonstrate an increasing level of stratification over time, and, correspondingly, the trajectory of a researcher's career is increasingly correlated with her entry point into the network.

Keywords

Associated Data

figshare | 10.6084/m9.figshare.c.6350496

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MeSH Term

Humans
Female
Authorship
Social Status
Biomedical Research
Social Networking

Word Cloud

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