Academic team formation as evolving hypergraphs

TL;DR

This paper investigates how academic collaboration teams form and evolve using hypergraphs, highlighting the importance of group interactions and semantic features in understanding team dynamics.

Contribution

It introduces a hypergraph-based framework to empirically analyze academic team formation, emphasizing the role of implicit group structures and repeated interactions.

Findings

Recurrent team formation is driven by implicit group structures.

Innovative research is not linked to more original teams.

There is polarization between expert-only and non-expert groups.

Abstract

This paper quantitatively explores the social and socio-semantic patterns of constitution of academic collaboration teams. To this end, we broadly underline two critical features of social networks of knowledge-based collaboration: first, they essentially consist of group-level interactions which call for team-centered approaches. Formally, this induces the use of hypergraphs and n-adic interactions, rather than traditional dyadic frameworks of interaction such as graphs, binding only pairs of agents. Second, we advocate the joint consideration of structural and semantic features, as collaborations are allegedly constrained by both of them. Considering these provisions, we propose a framework which principally enables us to empirically test a series of hypotheses related to academic team formation patterns. In particular, we exhibit and characterize the influence of an implicit group structure driving recurrent team formation processes. On the whole, innovative production does not appear to be correlated with more original teams, while a polarization appears between groups composed of experts only or non-experts only, altogether corresponding to collectives with a high rate of repeated interactions.