Modeling Collaboration in Academia: A Game Theoretic Approach

1. Modeling Collaboration in Academia: A Game Theoretic Approach Graham Cormode, Qiang Ma,S. Muthukrishnan, and Brian Thompson

2. Outline • Goal: Explore the use of Game Theory as a tool for modeling and understanding the dynamics of collaborative behavior • Contributions: • A model of academic collaboration supported by real-world publication data • The Academic Collaboration game, where researchers collaborate to maximize their academic success • Analysis of collaboration strategies and game equilibria Modeling Collaboration in Academia: A Game Theoretic Approach

3. Related Work • Model one researcher’s papers and citations over time [Hirsch’ 05] +6 +9 +6 +3 +3 +3 +6 +9 +6 +3 +3 +3 • Analyze the coauthorship graph [AAH’ 10, KPMVD’ 10] Modeling Collaboration in Academia: A Game Theoretic Approach

4. Our Approach We present the first generative model to describe the formation of academic collaborations, the resulting papers, and the citations they receive We model the system as a repeated game, where researchers choose collaborators each year in an attempt to maximize their long-term academic success Modeling Collaboration in Academia: A Game Theoretic Approach

5. Model Design and Validation • Hypothesis: is correlated with the academic success of its authors up to that point and the amount of effort they put into the paper • Dataset: DBLP + Google Scholar, 1M researchers, 2M publications • Experimental set-up: We consider three scenarios: • single-author paper, his/her only paper that year • two-author paper, their only paper that year • multiple papers by an author in the same year Modeling Collaboration in Academia: A Game Theoretic Approach

6. Model Design and Validation Observation: # of citations grows linearly with h-index Single-author, no other publications that year Modeling Collaboration in Academia: A Game Theoretic Approach

7. Model Design and Validation Observation: # of citations received by a paper is additive over the h-indices of the co-authors Two-author, no other publications that year Modeling Collaboration in Academia: A Game Theoretic Approach

8. Model Design and Validation Observation: # of citations received by an author is additive over multiple publications Multiple publications in the same year Modeling Collaboration in Academia: A Game Theoretic Approach

9. The Academic Collaboration Game Players: A set of researchers Utility: Each researcher wants to maximize his/her academic success as Actions: In year , each researcher can distribute units of “research potential” between individual and collaborative projects Outcome: Each project produces a paper that will receive citations equal to the total research potential invested by the authors Modeling Collaboration in Academia: A Game Theoretic Approach

10. Main Results • In the static multi-player game, each perfect matching on the researchers is in equilibrium • In the dynamic multi-player game, however, the perfect matchings are not in equilibrium A researcher’s h-index grows asymptotically faster when collaborating than when working independently – versus Modeling Collaboration in Academia: A Game Theoretic Approach

11. Take-away Messages Use of static rather than dynamic collaboration models may yield misleading predictions of people’s behavior in collaborative environments Game Theory is a promising tool for studying the dynamics of collaborative behavior The Academic Collaboration game can help study which metrics of academic success encourage behavior that benefits the academic community Modeling Collaboration in Academia: A Game Theoretic Approach

12. Future Directions Open question: Do there exist equilibria in the dynamic game? Extend the model to allow mixed strategies Analyze the game under other metrics of academic success besides the h-index Study the price of anarchy and stability under each of these scenarios Modeling Collaboration in Academia: A Game Theoretic Approach