Network Models for Teams with Overlapping Membership

Mengxiao Zhu, Yoav Bergner

Research output: Chapter in Book/Report/Conference proceedingChapter


Systems of teams with overlapping members arise in employment, training, and educational contexts. Team interdependence in these systems can confound analyses that aim to account for both individual and team attributes in studying team formation and performance. This chapter introduces bipartite networks for modeling teams with overlapping members. In these networks, individuals and teams are represented by two different types of nodes with links representing team affiliation. Two methods for analysis of bipartite networks with individual and team attributes are reviewed, exponential random graph models (ERGMs) and correspondence analysis (CA). Examples, discussions, and comparisons are provided for both methods.

Original languageEnglish (US)
Title of host publicationInnovative Assessment of Collaboration
PublisherSpringer Nature
Number of pages12
StatePublished - 2017

Publication series

NameMethodology of Educational Measurement and Assessment
ISSN (Print)2367-170X
ISSN (Electronic)2367-1718


  • Bipartite network
  • Correspondence analysis
  • Exponential random graph models (ERGMs)
  • Network model
  • Teams

ASJC Scopus subject areas

  • Education
  • Development


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