On Measuring the Diversity of Organizational Networks

Zeinab S. Jalali, Krishnaram Kenthapadi, Sucheta Soundarajan

Research output: Chapter in Book/Entry/PoemConference contribution


The interaction patterns of employees in social and professional networks play an important role in the success of employees and organizations as a whole. However, in many fields there is a severe under-representation of minority groups; moreover, minority individuals may be segregated from the rest of the network or isolated from one another. While the problem of increasing the representation of minority groups in various fields has been well-studied, diversification in terms of numbers alone may not be sufficient: social relationships should also be considered. In this work, we consider the problem of assigning a set of employment candidates to positions in a social network so that diversity and overall fitness are maximized, and propose Fair Employee Assignment (FairEA), a novel algorithm for finding such a matching. The output from FairEA can be used as a benchmark by organizations wishing to evaluate their hiring and assignment practices. On real and synthetic networks, we demonstrate that FairEA does well at finding high-fitness, high-diversity matchings.

Original languageEnglish (US)
Title of host publicationComplex Networks XII - Proceedings of the 12th Conference on Complex Networks CompleNet 2021
EditorsAndreia Sofia Teixeira, Diogo Pacheco, Marcos Oliveira, Hugo Barbosa, Bruno Gonçalves, Ronaldo Menezes
PublisherSpringer Science and Business Media B.V.
Number of pages14
ISBN (Print)9783030818531
StatePublished - 2021
Event12th International Conference on Complex Networks, CompleNet 2021 - Virtual, Online
Duration: May 24 2021May 26 2021

Publication series

NameSpringer Proceedings in Complexity
ISSN (Print)2213-8684
ISSN (Electronic)2213-8692


Conference12th International Conference on Complex Networks, CompleNet 2021
CityVirtual, Online

ASJC Scopus subject areas

  • Applied Mathematics
  • Modeling and Simulation
  • Computer Science Applications


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