Project

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

Applicant Schweitzer Frank
Number 140644
Funding scheme Interdisciplinary projects
Research institution Departement Management, Technologie und Ökonomie D-MTEC ETH Zürich
Institution of higher education ETH Zurich - ETHZ
Main discipline Economics
Start/End 01.05.2012 - 31.05.2016
Approved amount 492'111.00
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All Disciplines (2)

Discipline
Economics
Zoology

Keywords (4)

social bonding; network formation; social behaviour; rational strategies

Lay Summary (English)

Lead
Lay summary

Lead

Why do individuals establish social bonds? To answer that question we will combine in an interdisciplinary approach a unique long-term data set on social interactions in an animal society with formal models of network formation in economic and social systems.

Background

Social interactions play a crucial role in the lives of many organisms, including humans. Yet we still need to develop a comprehensive understanding of why individuals establish social bonds and how such interactions influence the complex social networks on the level of a larger group or population. Our project relies on the combination of knowledge, data and methods from both economics and animal behaviour. As an example of social organisation, we study a wild population of house mice in their natural environment, a barn near Zurich. Using automatic data recording methods and genetic analyses, we continuously document social interactions between individuals, and analyse relatedness and offspring production.

Goal

We intend to make a major contribution towards the scientific understanding of why individuals invest in the formation of social networks, by revealing the hidden principles underlying the decisions of their individual actors. Our goal is to expose the relation between reproductive success and social interaction strategies, both at the individual and at the population level.

Significance

By combining research about animal social behaviour and social network analysis in an innovative approach, our project demonstrates the importance of establishing individual social bonds in terms of long-term benefits gained by the individuals. The results will 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.  The project will make an important contribution, both theoretically and empirically, in identifying the incentive mechanisms that lead to the formation and the change of social networks.

Direct link to Lay Summary Last update: 21.02.2013

Responsible applicant and co-applicants

Employees

Publications

Publication
From Aristotle to Ringelmann: a large-scale analysis of team productivity and coordination in Open Source Software projects
Scholtes Ingo, Mavrodiev Pavlin, Schweitzer Frank (2016), From Aristotle to Ringelmann: a large-scale analysis of team productivity and coordination in Open Source Software projects, in Empirical Software Engineering, 21(2), 642-683.
Higher-order aggregate networks in the analysis of temporal networks: path structures and centralities
Scholtes Ingo, Wider Nicolas, Garas Antonios (2016), Higher-order aggregate networks in the analysis of temporal networks: path structures and centralities, in The European Physical Journal B, 89(3), 1-15.
Causality-driven slow-down and speed-up of diffusion in non-Markovian temporal networks
Scholtes Ingo, Wider Nicolas, Pfitzner René, Garas Antonios, Tessone Claudio J., Schweitzer Frank (2014), Causality-driven slow-down and speed-up of diffusion in non-Markovian temporal networks, in Nature Communications, 5, 5024-5024.
Nest attendance of lactating females in a wild house mouse population: Benefits associated with communal nesting
Auclair Yannick, König Barbara, Ferrari Manuela, Perony Nicolas, Lindholm Anna K. (2014), Nest attendance of lactating females in a wild house mouse population: Benefits associated with communal nesting, in Animal Behaviour, 143-149.
Predicting Scientific Success Based on Coauthorship Networks
Sarigol Emre, Pfitzner Rene, Scholtes Ingo, Garas Antonios, Schweitzer Frank (2014), Predicting Scientific Success Based on Coauthorship Networks, in EPJ Data Science, 3, 9.
Social resilience in online communities the autopsy of friendster
Garcia David, Mavrodiev Pavlin, Schweitzer Frank (2013), Social resilience in online communities the autopsy of friendster, in Proceedings of the 1st ACM Conference in Online Social Networks (COSN'13), Boston, Massachusetts, USAACM, New York, NY, USA.
The rise and fall of a central contributor: Dynamics of social organization and performance in the GENTOO community
Zanetti Marcelo Serrano, Scholtes Ingo, Tessone Claudio Juan, Schweitzer Frank (2013), The rise and fall of a central contributor: Dynamics of social organization and performance in the GENTOO community, in 2013 6th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE), San Francisco, CA, USAIEEE, USA.
How random is social behaviour? Disentangling social complexity through the study of a wild house mouse population.
Perony Nicolas, Tessone Claudio J, König Barbara, Schweitzer Frank (2012), How random is social behaviour? Disentangling social complexity through the study of a wild house mouse population., in PLOS computational biology, 8(11), 1002786-1002786.

Collaboration

Group / person Country
Types of collaboration
University of Zurich, Institute of Evolutionary Biology and Environmental Studies - Anna Lindholm Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Research Infrastructure

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
International Conference on Software Engineering (ICSE) Talk given at a conference From Aristotle to Ringelmann: A large-scale analysis of productivity and coordination in Open Source Software projects 18.05.2016 Austin, TX, United States of America Scholtes Ingo;
Winter Symposium Computational Social Science Talk given at a conference Mining Time-Stamped Network Data: Spectral Methods and Centrality Measures 01.12.2015 Köln, Germany Scholtes Ingo;
Research Seminar GESIS Individual talk Mining Social Organizations: A Network Perspective 30.11.2015 Köln, Germany Scholtes Ingo;
Research Seminar Channing Division of Network Medicine Individual talk Spectral Methods in the Analysis of Non-Markovian Temporal Networks 30.09.2015 Boston, MA, United States of America Scholtes Ingo;
Research Seminar Network Science Institute, Northeastern University Individual talk Analysis of Non-Markovian Temporal Networks: Spectral Methods and Centrality Measures 24.09.2015 Boston, MA, United States of America Scholtes Ingo;
Recognizing the Relevance of Change: Analysis and Control of Time-evolving Networks in Epidemiology and Evolutionary Medicine Talk given at a conference Analysis of Non-Markovian Temporal Networks 20.07.2015 Berlin, Germany Scholtes Ingo;
International School and Conference on Network Science (NetSci) 2014 Talk given at a conference Diffusion in Non-Markovian Temporal Networks: Slow-Down or Speed-Up? 06.06.2014 Berkley, United States of America Scholtes Ingo;
International School and Conference on Network Science (NetSci) 2014 Talk given at a conference How we collaborate - A complex network approach 04.06.2014 Berkley, California CA, United States of America Schweitzer Frank;
NetSci Satellite "Higher-Order Models in Network Science" Talk given at a conference Higher-Order Aggregate Representations of Temporal Networks 03.06.2014 Berkley, California CA, United States of America Scholtes Ingo;
NetSci Satellite "Multiple Network Modeling, Analysis and Mining Talk given at a conference Analysing temporal bipartite social networks 02.06.2014 Berkley, California CA, United States of America Schweitzer Frank;
Lorentz Center Workshop "Simulating the Social Processes of Science Talk given at a conference When your social position predicts your success: lessons from Open Source communities and citations 09.04.2014 Leiden, Netherlands Scholtes Ingo;
Invited Seminar Individual talk Success and Failure: A Complex Network Perspective 23.10.2013 University of Warwick, Great Britain and Northern Ireland Schweitzer Frank;
ECCS Satellite Quantifying Success Talk given at a conference Predicting success based on social network analysis 18.09.2013 Barcelona, Spain Scholtes Ingo;
Plenary talk at Max Planck Institute for Ornithology Individual talk At the corssroads between collective motion and social structure: What can we learn from a social perspective on movement ecology? 23.08.2013 Radolfzell, Germany Perony Nicolas;
Invited seminar, CoSy seminar series Individual talk Bridging the gap between social and spatial complexity in collective animal behaviour 15.05.2013 Uppsala University, Uppsala, Sweden Perony Nicolas;
Invited Seminar Individual talk Decoding social and spatial complexity in animal groups 07.12.2012 Radolfzell, Germany Perony Nicolas;
Collective Motion 2012 Talk given at a conference Leadership and information transfer in moving animal groups 09.11.2012 Bielefeld, Germany Perony Nicolas;
Invited seminar Individual talk On the interface between movement and sociality in animal behaviour (and what lies on either side) 13.09.2012 Santa Fe Institute, Santa Fe NM, United States of America Perony Nicolas;


Self-organised

Title Date Place
Symposium "Economic Networks" 20.05.2016 Zürich, Switzerland
Symposium "Computational Social Science" 06.11.2015 Zürich, Switzerland
NetSci Satellite "Higher-Order Models in Network Science" 03.06.2014 Berkeley, United States of America

Knowledge transfer events



Self-organised

Title Date Place
Quantifying scientific impact: networks, measures, insights? 12.02.2015 Zürich, Switzerland

Communication with the public

Communication Title Media Place Year
New media (web, blogs, podcasts, news feeds etc.) Social complexity on a perceptual landscape in a stochastic ABM model SimulPast International 2012
New media (web, blogs, podcasts, news feeds etc.) Zufall formt komplexe Sozialstruktur / Randomness forms complex social structures ETH Life International German-speaking Switzerland 2012

Awards

Title Year
ETH medal 2013

Abstract

In this interdisciplinary project we aim at studying the incentives ofsocial interaction and social bond formation by combining the analysis ofa unique long-term data set on social interactions in an animal societywith formal models of network formation in economic and social systems.Social interactions play a crucial role in the lives of many organisms,including humans. Yet we hardly understand why individuals establishsocial bonds, nor the way in which such interactions influence thecomplex social networks on the level of a larger group or population.We intend to make a major contribution towards the scientificunderstanding of social network formation, by revealing the hiddenprinciples underlying the strategic decisions of their individual actors.To fulfil this goal, we will undertake an interdisciplinary approachcombining knowledge, data and methods from both economics and animalbehaviour.As a model of social organisation, we will use a long-term data set onsocial interactions in a population of free-living mice in a barn nearZurich. We follow individually marked mice from cradle to grave oremigration out of the barn, continuously document all socialinteractions, and analyse genetic relatedness and offspring production.The latter allow us to use lifetime reproductive success as a measure foreach individual's biological fitness or success. We will use that dataset to test general hypotheses about the strategic interaction of agentson a microscopic, i.e. individual-based, level, to explain the observedstructure of social networks on a macroscopic, i.e. systemic, level. Someof these hypotheses will be tested by experimental manipulation of thesocial network (removal of individuals) in the study population of housemice.By integrating animal social behaviour and social network analysis, ourinnovative project will contribute to reveal the importance ofestablishing individual social bonds in terms of long-term benefitsgained by the individuals. The results will bring new insights into thelinks between the individual effort invested in social bonding, theresulting individual payoff, the position and role of agents in a networkand the overall network structure.
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