The role of social attraction and social avoidance in shaping modular networks
How interactions between individuals contribute to the emergence of complex societies is a major question in behavioural ecology. Nonetheless, little remains known about the type of immediate social structure (i.e. social network) that emerges from relationships that maximize beneficial interactions...
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| Format: | Article |
| Language: | English |
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The Royal Society
2024-02-01
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| Series: | Royal Society Open Science |
| Subjects: | |
| Online Access: | https://royalsocietypublishing.org/doi/10.1098/rsos.231619 |
| _version_ | 1797293321064808448 |
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| author | Valéria Romano Ivan Puga-Gonzalez Andrew J. J. MacIntosh Cédric Sueur |
| author_facet | Valéria Romano Ivan Puga-Gonzalez Andrew J. J. MacIntosh Cédric Sueur |
| author_sort | Valéria Romano |
| collection | DOAJ |
| description | How interactions between individuals contribute to the emergence of complex societies is a major question in behavioural ecology. Nonetheless, little remains known about the type of immediate social structure (i.e. social network) that emerges from relationships that maximize beneficial interactions (e.g. social attraction towards informed individuals) and minimize costly relationships (e.g. social avoidance of infected group mates). We developed an agent-based model where individuals vary in the degree to which individuals signal benefits versus costs to others and, on this basis, choose with whom to interact depending on simple rules of social attraction (e.g. access to the highest benefits) and social avoidance (e.g. avoiding the highest costs). Our main findings demonstrate that the accumulation of individual decisions to avoid interactions with highly costly individuals, but that are to some extent homogeneously beneficial, leads to more modular networks. On the contrary, individuals favouring interactions with highly beneficial individuals, but that are to some extent homogeneously costly, lead to less modular networks. Interestingly, statistical models also indicate that when individuals have multiple potentially beneficial partners to interact with, and no interaction cost exists, this also leads to more modular networks. Yet, the degree of modularity is contingent upon the variability in benefit levels held by individuals. We discuss the emergence of modularity in the systems and their consequences for understanding social trade-offs. |
| first_indexed | 2024-03-07T20:11:10Z |
| format | Article |
| id | doaj.art-b0ccd752979b4ce592f0328ca55d91fa |
| institution | Directory Open Access Journal |
| issn | 2054-5703 |
| language | English |
| last_indexed | 2024-03-07T20:11:10Z |
| publishDate | 2024-02-01 |
| publisher | The Royal Society |
| record_format | Article |
| series | Royal Society Open Science |
| spelling | doaj.art-b0ccd752979b4ce592f0328ca55d91fa2024-02-28T00:05:50ZengThe Royal SocietyRoyal Society Open Science2054-57032024-02-0111210.1098/rsos.231619The role of social attraction and social avoidance in shaping modular networksValéria Romano0Ivan Puga-Gonzalez1Andrew J. J. MacIntosh2Cédric Sueur3IMBE, Aix Marseille Univ., Avignon Univ., CNRS, IRD, Marseille, FranceCenter for Modelling Social Systems (CMSS) at NORCE, Kristiansand, NorwayWildlife Research Center, Kyoto University, Inuyama Campus, Inuyama, JapanUniversité de Strasbourg, CNRS, IPHC UMR 7178, 67000 Strasbourg, FranceHow interactions between individuals contribute to the emergence of complex societies is a major question in behavioural ecology. Nonetheless, little remains known about the type of immediate social structure (i.e. social network) that emerges from relationships that maximize beneficial interactions (e.g. social attraction towards informed individuals) and minimize costly relationships (e.g. social avoidance of infected group mates). We developed an agent-based model where individuals vary in the degree to which individuals signal benefits versus costs to others and, on this basis, choose with whom to interact depending on simple rules of social attraction (e.g. access to the highest benefits) and social avoidance (e.g. avoiding the highest costs). Our main findings demonstrate that the accumulation of individual decisions to avoid interactions with highly costly individuals, but that are to some extent homogeneously beneficial, leads to more modular networks. On the contrary, individuals favouring interactions with highly beneficial individuals, but that are to some extent homogeneously costly, lead to less modular networks. Interestingly, statistical models also indicate that when individuals have multiple potentially beneficial partners to interact with, and no interaction cost exists, this also leads to more modular networks. Yet, the degree of modularity is contingent upon the variability in benefit levels held by individuals. We discuss the emergence of modularity in the systems and their consequences for understanding social trade-offs.https://royalsocietypublishing.org/doi/10.1098/rsos.231619group-livingsocial trade-offinteraction costs and benefitsbehavioural variationcomplex systemagent-based model |
| spellingShingle | Valéria Romano Ivan Puga-Gonzalez Andrew J. J. MacIntosh Cédric Sueur The role of social attraction and social avoidance in shaping modular networks Royal Society Open Science group-living social trade-off interaction costs and benefits behavioural variation complex system agent-based model |
| title | The role of social attraction and social avoidance in shaping modular networks |
| title_full | The role of social attraction and social avoidance in shaping modular networks |
| title_fullStr | The role of social attraction and social avoidance in shaping modular networks |
| title_full_unstemmed | The role of social attraction and social avoidance in shaping modular networks |
| title_short | The role of social attraction and social avoidance in shaping modular networks |
| title_sort | role of social attraction and social avoidance in shaping modular networks |
| topic | group-living social trade-off interaction costs and benefits behavioural variation complex system agent-based model |
| url | https://royalsocietypublishing.org/doi/10.1098/rsos.231619 |
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