Social transmission in networks: global efficiency peaks with intermediate levels of modularity
- 215 Downloads
In myriad biological systems, multiple lines of evidence indicate that modularity, wherein parts of a network are organized into modules such as subgroups in animal networks, may affect social transmission processes. In animal societies, there is increased interest in understanding variation in the effects of modularity on transmission as it may provide important insight into a given network’s performance, in addition to the evolutionary consequences the structure of the network may have for individual fitness. Yet, to our knowledge, the degree to which network efficiency is modularity dependent has not yet been investigated in great detail in behavioral and evolutionary ecology. Here, we investigated to what degree network efficiency, as a proxy for social transmission, is modularity dependent. We created 2798 networks varying in group size and density, and tested whether network structure (density, Newman’s modularity, eigenvector centralization) and group size shape network efficiency. We also used published data from 41 primate social networks to test whether the predictions generated in our simulations were supported by empirical observations. Our results show a non-linear relationship between modularity and global efficiency, with the latter peaking at intermediate values of modularity in both theoretical and empirical networks. This phenomenon may have relevance for observed variation in social structure and its link with network performance. Our results may thus provide a basis from which to discuss the evolution of complex systems such as animal societies.
Networks may maximize performance and minimize transmission costs, as demonstrated in neural networks, but to what degree network efficiency is modularity dependent has not yet been investigated in behavioral ecology. We provide evidence that modularity, such as subgrouping in animal networks, can have non-linear effects on transmission processes, with low values of modularity tending to positively influence social transmission and high values tending to negatively influence transmission. This pattern was consistent across small, medium, and large social groups from theoretical networks, and was corroborated by our empirical networks which were derived from 41 small- to medium-sized groups of 15 primate species. These results have potential implications for the understanding of social flexibility and its link with network performance, in addition informing many interdisciplinary fields, such as communication and computer science.
KeywordsGlobal efficiency Subgrouping Theoretical and biological networks Transmission process Social behavior
We acknowledge Damien Farine for his comments on an earlier version of this manuscript, as well as Friederike Hillemann and two other reviewers who significantly contributed to the enhancement of this work. We also acknowledge Xavier Meyer for his help implementing the codes for Figs. 2 and 3.
V.R., C.S., and A.J.J.M. conceptualized the study. M.S. created the theoretical networks and conducted exploratory analyses; V.R. performed statistical analyses and wrote the manuscript; A.J.J.M. and C.S. significantly contributed to the manuscript development; M.S. and J.P. provided additional comments.
V.R. was supported by the Brazilian Ministry of Education (CAPES), A.J.J.M. was supported by Grants-in-Aid from the Japan Society for the Promotion of Science (JSPS), and C.S. was funded by the University of Strasbourg Institute for Advanced Studies (USIAS), by an ANR program Blanc grant (HANC, ANR-15-CE36-0005-01) and a CNRS PICS program (exchange with Japan, no. 7455). V.R. also received support from the JSPS.
- Barabási AL (2016) Network science. Cambridge University Press, CambridgeGoogle Scholar
- Csárdi G, Nepusz T (2006) The igraph software package for complex network research. Int J Complex Syst 1695:1–9Google Scholar
- Field A, Miles J, Field Z (2012) Discovering statistics using R. SAGE Publications Ltd, Thousand OaksGoogle Scholar
- Muggeo VMR (2008) Segmented: an R package to fit regression models with broken-line relationships. R News 8:20–25Google Scholar
- Nunn CL, Jordán F, McCabe CM, Verdolin JL, Fewell JH (2015) Infectious disease and group size: more than just a numbers game. Philos Trans R Soc B 370:2014011Google Scholar
- Plowright W (1982) The effects of rinderpest and rinderpest control on wildlife in Africa. Symp Zool Soc 50:1–28Google Scholar
- Romano V (2017) Social networks as a trade-off between optimal information transmission and reduced disease transmission. Dissertation, Université de StrasbourgGoogle Scholar
- Scott J (2017) Social network analysis. Sage Publications Ltd, Thousand OaksGoogle Scholar
- Sueur C (2011) Social network, information flow and decision-making efficiency: a comparison of humans and animals. In: Safar M, Mahdi K (eds) Social networking and community behavior modeling: qualitative and quantitative measures, 1st edn. IGI Global, Hershey, pp 164–177Google Scholar
- Walsh PD, Bermejo M, Rodríguez-Teijeiro JD (2009) Disease avoidance and the evolution of primate social connectivity: ebola, bats, gorillas, and chimpanzees. In: Huffman M, Chapman CA (eds) Primate parasite ecology: the dynamics and study of host–parasite relationships, 1st edn. Cambridge University Press, Cambridge, pp 183–198Google Scholar