scholarly journals Cultural Selection Shapes Network Structure

2018 ◽  
Author(s):  
Marco Smolla ◽  
Erol Akcay
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Cultural Evolution ◽  
Level Structure ◽  
Population Level ◽  
Ecological Trap ◽  
Trade Off ◽  
Cultural Selection ◽  
Dynamic Social Networks ◽  
The Social

Cultural evolution relies on the social transmission of cultural traits across a population, along the ties of an underlying social network that emerges from non-random interactions among individuals. Research indicates that the structure of those interaction networks affects information spread, and thus a population's ability for cumulative culture. However, how network structure itself is driven by population-culture co-evolution remains largely unclear. We use a simple but realistic model of complex dynamic social networks to investigate how populations negotiate the trade-off between acquiring new skills and getting better at existing skills, and how this trade-off, in turn, shapes the social structure of the population. Our results reveal unexpected eco-evolutionary feedback from culture onto social network structure and vice versa. We show that selecting for generalists (favouring a broad repertoire of skills) results in sparsely connected networks with highly diverse skill sets, whereas selecting for specialists (favouring skill proficiency) results in densely connected networks and a population that specializes on the same few skills on which everyone is an expert. Surprisingly, cultural selection for specialisation can act as an 'ecological trap' where it can take a long time for a specialist population to adapt to a generalist world. Our model advances our understanding of the complex feedbacks in cultural evolution and demonstrates how individual-level behaviour can lead to the emergence of population-level structure.

scholarly journals Cultural selection shapes network structure

2019 ◽  
Vol 5 (8) ◽  
pp. eaaw0609 ◽  
Author(s):  
Marco Smolla ◽  
Erol Akçay
Keyword(s):  
Social Networks ◽  
Network Structure ◽  
Cultural Evolution ◽  
Level Structure ◽  
Population Level ◽  
Trade Off ◽  
Skill Sets ◽  
Individual Level ◽  
Dense Networks ◽  
The Social

Cultural evolution relies on the social transmission of cultural traits along a population’s social network. Research indicates that network structure affects information spread and thus the capacity for cumulative culture. However, how network structure itself is driven by population-culture co-evolution remains largely unclear. We use a simple model to investigate how populations negotiate the trade-off between acquiring new skills and getting better at existing skills and how this trade-off shapes social networks. We find unexpected eco-evolutionary feedbacks from culture onto social networks and vice versa. We show that selecting for skill generalists results in sparse networks with diverse skill sets, whereas selecting for skill specialists results in dense networks and a population that specializes on the same few skills on which everyone is an expert. Our model advances our understanding of the complex feedbacks in cultural evolution and demonstrates how individual-level behavior can lead to the emergence of population-level structure.

scholarly journals Formation of raiding parties for intergroup violence is mediated by social network structure

2016 ◽  
Vol 113 (43) ◽  
pp. 12114-12119 ◽  
Author(s):  
Luke Glowacki ◽  
Alexander Isakov ◽  
Richard W. Wrangham ◽  
Rose McDermott ◽  
James H. Fowler ◽  
...  
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Social Dynamics ◽  
Small Scale ◽  
East African ◽  
Nomadic Pastoralists ◽  
Social Network Structure ◽  
The Social ◽  
Total Impact ◽  
Social Network Position

Intergroup violence is common among humans worldwide. To assess how within-group social dynamics contribute to risky, between-group conflict, we conducted a 3-y longitudinal study of the formation of raiding parties among the Nyangatom, a group of East African nomadic pastoralists currently engaged in small-scale warfare. We also mapped the social network structure of potential male raiders. Here, we show that the initiation of raids depends on the presence of specific leaders who tend to participate in many raids, to have more friends, and to occupy more central positions in the network. However, despite the different structural position of raid leaders, raid participants are recruited from the whole population, not just from the direct friends of leaders. An individual’s decision to participate in a raid is strongly associated with the individual’s social network position in relation to other participants. Moreover, nonleaders have a larger total impact on raid participation than leaders, despite leaders’ greater connectivity. Thus, we find that leaders matter more for raid initiation than participant mobilization. Social networks may play a role in supporting risky collective action, amplify the emergence of raiding parties, and hence facilitate intergroup violence in small-scale societies.

The social network structure of a semi-free roaming European bison herd (Bison bonasus)

2019 ◽  
Vol 158 ◽  
pp. 97-105 ◽  
Author(s):  
Amandine Ramos ◽  
Lola Manizan ◽  
Esther Rodriguez ◽  
Yvonne J.M. Kemp ◽  
Cédric Sueur
Keyword(s):  
Social Network ◽  
Network Structure ◽  
European Bison ◽  
Bison Bonasus ◽  
Social Network Structure ◽  
The Social

scholarly journals Dynamic social networks and the implications for the spread of infectious disease

2008 ◽  
Vol 5 (26) ◽  
pp. 1001-1007 ◽  
Author(s):  
Jonathan M Read ◽  
Ken T.D Eames ◽  
W. John Edmunds
Keyword(s):  
Social Network ◽  
Close Contact ◽  
Peer Group ◽  
Quantitative Description ◽  
Effective Control ◽  
Dynamic Social Networks ◽  
The Social ◽  
The Stability ◽  
The Impact ◽  
Casual Contact

Understanding the nature of human contact patterns is crucial for predicting the impact of future pandemics and devising effective control measures. However, few studies provide a quantitative description of the aspects of social interactions that are most relevant to disease transmission. Here, we present the results from a detailed diary-based survey of casual (conversational) and close contact (physical) encounters made by a small peer group of 49 adults who recorded 8661 encounters with 3528 different individuals over 14 non-consecutive days. We find that the stability of interactions depends on the intimacy of contact and social context. Casual contact encounters mostly occur in the workplace and are predominantly irregular, while close contact encounters mostly occur at home or in social situations and tend to be more stable. Simulated epidemics of casual contact transmission involve a large number of non-repeated encounters, and the social network is well captured by a random mixing model. However, the stability of the social network should be taken into account for close contact infections. Our findings have implications for the modelling of human epidemics and planning pandemic control policies based on social distancing methods.

scholarly journals Offspring social network structure predicts fitness in families

2012 ◽  
Vol 279 (1749) ◽  
pp. 4914-4922 ◽  
Author(s):  
Nick J. Royle ◽  
Thomas W. Pike ◽  
Philipp Heeb ◽  
Heinz Richner ◽  
Mathias Kölliker
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Structure ◽  
Conflicts Of Interest ◽  
Parus Major ◽  
Social Structures ◽  
Emergent Properties ◽  
Social Network Structure ◽  
The Social ◽  
The Individual

Social structures such as families emerge as outcomes of behavioural interactions among individuals, and can evolve over time if families with particular types of social structures tend to leave more individuals in subsequent generations. The social behaviour of interacting individuals is typically analysed as a series of multiple dyadic (pair-wise) interactions, rather than a network of interactions among multiple individuals. However, in species where parents feed dependant young, interactions within families nearly always involve more than two individuals simultaneously. Such social networks of interactions at least partly reflect conflicts of interest over the provision of costly parental investment. Consequently, variation in family network structure reflects variation in how conflicts of interest are resolved among family members. Despite its importance in understanding the evolution of emergent properties of social organization such as family life and cooperation, nothing is currently known about how selection acts on the structure of social networks. Here, we show that the social network structure of broods of begging nestling great tits Parus major predicts fitness in families. Although selection at the level of the individual favours large nestlings, selection at the level of the kin-group primarily favours families that resolve conflicts most effectively.

The social network structure of a wild meerkat population: 2. Intragroup interactions

2009 ◽  
Vol 64 (1) ◽  
pp. 81-95 ◽  
Author(s):  
Joah R. Madden ◽  
Julian A. Drewe ◽  
Gareth P. Pearce ◽  
Tim H. Clutton-Brock
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Social Network Structure ◽  
The Social

Estimating Policy Positions Using Social Network Data

2016 ◽  
Vol 35 (1) ◽  
pp. 53-67 ◽  
Author(s):  
Alejandro Ecker
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Science Research ◽  
Policy Position ◽  
Policy Positions ◽  
Political Actors ◽  
External Data ◽  
Social Network Structure ◽  
Big Data Applications ◽  
The Social

Social network site (SNS) data provide scholars with a plethora of new opportunities for studying public opinion and forecasting electoral outcomes. While these are certainly among the most promising big data applications in political science research, a series of pioneering studies have started to uncover the vast potential of such data to estimate the policy positions of political actors. Adding to this emerging strand in the scholarly literature, the present article explores the validity of (individual) policy positions derived from the social network structure of the microblogging platform Twitter. At the aggregate party level, cross-validation with external data sources suggests that SNS data provide valid policy position estimates. In contrast, the empirical analysis reveals only a moderate connection between individual policy positions retrieved from the social network structure and those retrieved from members of parliament individual voting record. These results thus highlight the potential as well as important limitations of SNS data in indicating the policy positions of political parties and individual legislators.

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