Modeling Collaboration in Academia: A Game Theoretic Approach

TL;DR

This paper introduces a game-theoretic model to analyze academic collaboration, demonstrating that collaboration is incentivized and influencing citation outcomes, supported by real-world data analysis.

Contribution

It develops the h-Reinvestment model and applies game theory to understand researcher collaboration dynamics and incentives.

Findings

Strong incentive for researchers to collaborate over working alone

Collaboration positively impacts citation counts

Game-theoretic analysis reveals strategic collaboration behaviors

Abstract

In this work, we aim to understand the mechanisms driving academic collaboration. We begin by building a model for how researchers split their effort between multiple papers, and how collaboration affects the number of citations a paper receives, supported by observations from a large real-world publication and citation dataset, which we call the h-Reinvestment model. Using tools from the field of Game Theory, we study researchers' collaborative behavior over time under this model, with the premise that each researcher wants to maximize his or her academic success. We find analytically that there is a strong incentive to collaborate rather than work in isolation, and that studying collaborative behavior through a game-theoretic lens is a promising approach to help us better understand the nature and dynamics of academic collaboration.