A game-theory modeling approach to utility and strength of interactions dynamics in biomedical research social networks

• Published in: Complex adaptive systems modeling 2017-05, Vol.5 (1), p.1, Article 5
• Main Authors: Siqueiros-García, J. Mario, García-Herrera, Rodrigo, Hernández-Lemus, Enrique, Alcalá-Corona, Sergio
• Format: Article
• Language: English
• Subjects: Biomedical research; Collaboration; Complex Systems; Computer simulation; Game theory; Management Science; Mathematics; Mathematics and Statistics; Maximization; Operations Research; Operations Research/Decision Theory; Players; Researchers; Scientists; Simulation and Modeling; Strength; Topology; Utilities
• ISSN: 2194-3206; 2194-3206
• DOI: 10.1186/s40294-017-0044-0

Purpose Collaboration has become a cornerstone in biomedical research today. In contrast to physics which has a long history and experience in collaborative projects, biology is only recently becoming an evermore collaborative discipline. In this article we explore the effect of a collaboration network on the distribution of players having access to certain amount of resources from other players in the network and the distribution of the strength of interactions among them. We are interested in how they affect each other in the context of a network of scientific collaboration under the idea that while researchers are interested in maximizing their utilities, they also know that it is important to invest in building collaborative relationships. Methods We implemented two games played simultaneously: one for maximizing individual utility based on the iterated prisoner’s dilemma; the other, a coordination game for maximizing the connection strength between players. We tested our simulation on a biomedical research community network in México and compared the results with Erdös–Renyí, a Watts–Strogatz small-world and Barabási–Albert topologies. Results Different topologies display different global utility and global strength of interaction distributions. Moreover, the distribution of utility and strength of interaction in the researchers network is similar to that of Barabási–Albert and Watts–Strogatz topologies, respectively. Conclusions Data related to Science, from co-authorships to Scientists' movility are increasingly becoming available. We think that the readiness of these sort of data is a great opportunity for scientists interested in the social dynamics of science, especially in the context of computational social science.