Payoffs of local and global network structures: Reproductive career paths in wild house mice

This project is related to our research lines: Structure and dynamics of animal societies and Structure and dynamics of online social networks

Duration 36 months (May 2012 - April 2015)

Funding source Swiss National Science Foundation (Grant CR31I1_140644 / 1)

Project partner until November 2013: Prof. Barbara König, Evolutionary Biology and Environmental Studies, University of Zurich (Switzerland)


Why do individuals establish social bonds? To answer that question we focus our data-driven modeling approach on social interactions in animal societies and humans. Specifically, in the first part of the project we analyse data obtained from a wild population of house mice in their natural environment. In the second part, we extend our studies to analyse also collaboration networks of scientists and software developers. The project is really interdisciplinary, as it combines methods from different domains (social network analysis, machine learning, agent-based modeling) to analyse longitudinal and panel data from various realms. 

We aim at a comprehensive understanding why individuals invest in the formation of social networks, by revealing the hidden principles underlying their decisions. Our goal is to expose the relation between success and social interaction strategies, both at the individual level and at the level of larger groups. For these, different measures of success apply, e.g. the number of offsprings in animals, the number of citations in scientific publications, the number of bugs fixed by developers. Fine grained data about the social interactions of the actors, e.g. the co-location or inheritance network of mice, the co-authorship network of scientists and the assignments between developers, allow us to relate success and strategic behavior in a statistical manner, for which we particularly apply machine-learning approaches. 

The project makes an important contribution, both theoretically and empirically, in identifying the incentive mechanisms that lead to the formation and the change of social networks. Our results shed new light on the relations between the individual effort invested in social bonding, the resulting individual payoff, as well as the position and role of individuals in a network. 







Related Publications

Predicting Scientific Success Based on Coauthorship Networks

Sarigol, Emre; Pfitzner, Rene; Scholtes, Ingo; Garas, Antonios; Schweitzer, Frank

EPJ Data Science, pages: 9, volume: 3


Nest attendance of lactating females in a wild house mouse population: Benefits associated with communal nesting

Auclair, Yannick; Koenig, Barbara; Ferrari, Manuela; Perony, Nicolas; Lindholm, Anna K.

Animal Behaviour, pages: 143-149, number: 92


How random is social behaviour? Disentangling social complexity through the study of a wild house mouse population

Perony, Nicolas; Tessone, Claudio Juan; Koenig, Barbara; Schweitzer, Frank

PLOS Computational Biology, pages: e1002786, volume: 8, number: 11


A stochastic model of social interaction in wild house mice

Perony, Nicolas; Koenig, Barbara; Schweitzer, Frank

Proceedings of the European Conference on Complex Systems 2010