Rank-dependent social inheritance determines social network structure in spotted hyenas

Science ◽  
2021 ◽  
Vol 373 (6552) ◽  
pp. 348-352
Author(s):  
Amiyaal Ilany ◽  
Kay E. Holekamp ◽  
Erol Akçay
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Interactions ◽  
Social Rank ◽  
Relationship Strength ◽  
Social Network Structure ◽  
Spotted Hyenas ◽  
Using Data ◽  
Degree Of Similarity ◽  
Animal Social Networks

The structure of animal social networks influences survival and reproductive success, as well as pathogen and information transmission. However, the general mechanisms determining social structure remain unclear. Using data from 73,767 social interactions among wild spotted hyenas collected over 27 years, we show that the process of social inheritance determines how offspring relationships are formed and maintained. Relationships between offspring and other hyenas bear resemblance to those of their mothers for as long as 6 years, and the degree of similarity increases with maternal social rank. Mother-offspring relationship strength affects social inheritance and is positively correlated with offspring longevity. These results support the hypothesis that social inheritance of relationships can structure animal social networks and be subject to adaptive tradeoffs.

scholarly journals Rank-dependent social inheritance determines social network structure in a wild mammal population

2020 ◽  
Author(s):  
Amiyaal Ilany ◽  
Kay E. Holekamp ◽  
Erol Akçay
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Interactions ◽  
Social Rank ◽  
Wild Mammal ◽  
Social Network Structure ◽  
Spotted Hyenas ◽  
Using Data ◽  
Degree Of Similarity ◽  
Animal Social Networks

AbstractThe structure of animal social networks influences survival and reproductive success, as well as pathogen and information transmission. However, the general mechanisms determining social structure remain unclear. Using data on 73,767 social interactions among wild spotted hyenas over 27 years, we show that a process of social inheritance determines how offspring relationships are formed and maintained. The relationships of offspring with other hyenas are similar to those of their mothers over up to six years, and the degree of similarity increases with maternal social rank. The strength of mother-offspring relationship affects social inheritance and is positively correlated with offspring longevity. These results confirm the hypothesis that social inheritance of relationships can structure animal social networks and be subject to adaptive tradeoffs.

scholarly journals How demographic processes shape animal social networks

2019 ◽  
Vol 31 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Daizaburo Shizuka ◽  
Allison E Johnson
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Structure ◽  
Network Structure ◽  
Evolutionary Dynamics ◽  
Social Connections ◽  
Social Network Structure ◽  
The Social ◽  
Demographic Processes ◽  
Animal Social Networks

Abstract Demographic processes play a key role in shaping the patterns of social relations among individuals in a population. Social network analysis is a powerful quantitative tool for assessing the social structure formed by associations between individuals. However, demographic processes are rarely accounted for in such analyses. Here, we summarize how the structure of animal social networks is shaped by the joint effects of social behavior and turnover of individuals and suggest how a deeper understanding of these processes can open new, exciting avenues for research. Death or dispersal can have the direct effect of removing an individual and all its social connections, and can also have indirect effects, spurring changes in the distribution of social connections between remaining individuals. Recruitment and integration of juveniles and immigrant into existing social networks are critical to the emergence and persistence of social network structure. Together, these behavioral responses to loss and gain of social partners may impact how societies respond to seasonal or catastrophic turnover events. The fitness consequences of social position (e.g., survival and reproductive rates) may also create feedback between the social network structure and demography. Understanding how social structure changes in response to turnover of individuals requires further integration between long-term field studies and network modeling methods. These efforts will likely yield new insights into the connections between social networks and life history, ecological change, and evolutionary dynamics.

scholarly journals The switching mechanisms of social network densification

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Teruyoshi Kobayashi ◽  
Mathieu Génois
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Context ◽  
Social Interactions ◽  
Regime Switching ◽  
Face To Face ◽  
The Social ◽  
Switching Property ◽  
Distinctive Type ◽  
Insight Into

AbstractDensification and sparsification of social networks are attributed to two fundamental mechanisms: a change in the population in the system, and/or a change in the chances that people in the system are connected. In theory, each of these mechanisms generates a distinctive type of densification scaling, but in reality both types are generally mixed. Here, we develop a Bayesian statistical method to identify the extent to which each of these mechanisms is at play at a given point in time, taking the mixed densification scaling as input. We apply the method to networks of face-to-face interactions of individuals and reveal that the main mechanism that causes densification and sparsification occasionally switches, the frequency of which depending on the social context. The proposed method uncovers an inherent regime-switching property of network dynamics, which will provide a new insight into the mechanics behind evolving social interactions.

scholarly journals Inequality is rising where social network segregation interacts with urban topology

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Gergő Tóth ◽  
Johannes Wachs ◽  
Riccardo Di Clemente ◽  
Ákos Jakobi ◽  
Bence Ságvári ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Structure ◽  
Urban Geography ◽  
Online Social Network ◽  
Stage Model ◽  
Significant Relationships ◽  
Social Segregation ◽  
Social Network Structure ◽  
Physical Barriers

AbstractSocial networks amplify inequalities by fundamental mechanisms of social tie formation such as homophily and triadic closure. These forces sharpen social segregation, which is reflected in fragmented social network structure. Geographical impediments such as distance and physical or administrative boundaries also reinforce social segregation. Yet, less is known about the joint relationships between social network structure, urban geography, and inequality. In this paper we analyze an online social network and find that the fragmentation of social networks is significantly higher in towns in which residential neighborhoods are divided by physical barriers such as rivers and railroads. Towns in which neighborhoods are relatively distant from the center of town and amenities are spatially concentrated are also more socially segregated. Using a two-stage model, we show that these urban geography features have significant relationships with income inequality via social network fragmentation. In other words, the geographic features of a place can compound economic inequalities via social networks.

scholarly journals Balancing User Profile and Social Network Structure for Anchor Link Inferring Across Multiple Online Social Networks

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 12031-12040 ◽  
Author(s):  
Jiangtao Ma ◽  
Yaqiong Qiao ◽  
Guangwu Hu ◽  
Yongzhong Huang ◽  
Meng Wang ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Structure ◽  
Online Social Networks ◽  
User Profile ◽  
Social Network Structure

scholarly journals Head-to-Head Comparison of Social Network Assessments in Stroke Survivors

2020 ◽  
Vol 11 (1) ◽  
pp. 18-24
Author(s):  
Morgan Prust ◽  
Abby Halm ◽  
Simona Nedelcu ◽  
Amber Nieves ◽  
Amar Dhand
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Social Network ◽  
Social Isolation ◽  
Network Structure ◽  
Network Size ◽  
Personal Network ◽  
Mapping Tool ◽  
Social Network Structure ◽  
Network Mapping

Background and Purpose: Social networks influence human health and disease through direct biological and indirect psychosocial mechanisms. They have particular importance in neurologic disease because of support, information, and healthy behavior adoption that circulate in networks. Investigations into social networks as determinants of disease risk and health outcomes have historically relied on summary indices of social support, such as the Lubben Social Network Scale–Revised (LSNS-R) or the Stroke Social Network Scale (SSNS). We compared these 2 survey tools to personal network (PERSNET) mapping tool, a novel social network survey that facilitates detailed mapping of social network structure, extraction of quantitative network structural parameters, and characterization of the demographic and health parameters of each network member. Methods: In a cohort of inpatient and outpatient stroke survivors, we administered LSNS-R, SSNS, and PERSNET in a randomized order to each patient. We used logistic regression to generate correlation matrices between LSNS-R scores, SSNS scores, and PERSNET’s network structure (eg, size and density) and composition metrics (eg, percent kin in network). We also examined the relationship between LSNS-R-derived risk of social isolation with PERSNET-derived network size. Results: We analyzed survey responses for 67 participants and found a significant correlation between LSNS-R, SSNS, and PERSNET-derived indices of network structure. We found no correlation between LSNS-R, SSNS, and PERSNET-derived metrics of network composition. Personal network mapping tool structural and compositional variables were also internally correlated. Social isolation defined by LSNS-R corresponded to a network size of <5. Conclusions: Personal network mapping tool is a valid index of social network structure, with a significant correlation to validated indices of perceived social support. Personal network mapping tool also captures a novel range of health behavioral data that have not been well characterized by previous network surveys. Therefore, PERSNET offers a comprehensive social network assessment with visualization capabilities that quantifies the social environment in a valid and unique manner.

scholarly journals GRANDPARENT CAREGIVERS: THE RELATION BETWEEN SOCIAL NETWORKS AND RESILIENCE

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S678-S679
Author(s):  
Nancy Mendoza ◽  
Christine Fruhauf
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Social Network ◽  
Future Research ◽  
Grandparents Raising Grandchildren ◽  
Face To Face ◽  
Grandparent Caregivers ◽  
New Information ◽  
Multiple Challenges ◽  
Using Data

Abstract Grandparents raising grandchildren experience multiple challenges as they take on the unexpected role of caring for their grandchildren, which usually occurs under stressful and stigmatizing conditions. Many of the challenges grandparents experience are well documented in the research. Less attention is given to understanding how a grandparent caregiver’s social network changes when s/he becomes a caregiver and how her/his social network influences resilience. Thus, the purpose of this study was to use social network analysis (SNA) to examine the relation between social networks and resilience in grandparents raising their grandchildren. This was done by conducting face-to-face interviews with twenty grandparents raising grandchildren after they completed a survey measuring social support, social isolation, and resilience. The interview protocol included questions related to participants’ social network, social support, and services. Prior to the interviews, using data from the surveys participants were identified as representing one of four resilience quadrants: resilient, maladaptive, competent, and vulnerable. Qualitative analysis of grandparent’s social networks across groups indicated resilient grandparent caregivers’ networks were structured in a way that provided more opportunities for the inflow of new information and resources. Whereas the proportion of professionals in maladaptive grandparent caregivers’ networks tended to be less than for other networks. This could suggest that for grandparent caregivers, having professionals in one’s network can be beneficial. Findings from the current study provide opportunities for future research such as identifying ways to help grandparent caregivers structure their social networks to promote resilience.

scholarly journals Identifying Social Network Conditions that Facilitate Sedentary Behavior Change: The Benefit of Being a “Bridge” in a Group-based Intervention

2020 ◽  
Vol 17 (12) ◽  
pp. 4197 ◽  
Author(s):  
Sabina B. Gesell ◽  
Kayla de la Haye ◽  
Evan C. Sommer ◽  
Santiago J. Saldana ◽  
Shari L. Barkin ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Behavior Change ◽  
Sedentary Behavior ◽  
Small Group ◽  
Markov Models ◽  
Healthy Lifestyle ◽  
Multilevel Regression ◽  
Using Data ◽  
The Individual

Using data from one of the first trials to try to leverage social networks as a mechanism for obesity intervention, we examined which social network conditions amplified behavior change. Data were collected as part of a community-based healthy lifestyle intervention in Nashville, USA, between June 2014 and July 2017. Adults randomized to the intervention arm were assigned to a small group of 10 participants that met in person for 12 weekly sessions. Intervention small group social networks were measured three times; sedentary behavior was measured by accelerometry at baseline and 12 months. Multivariate hidden Markov models classified people into distinct social network trajectories over time, based on the structure of the emergent network and where the individual was embedded. A multilevel regression analysis assessed the relationship between network trajectory and sedentary behavior (N = 261). Being a person that connected clusters of intervention participants at any point during the intervention predicted an average reduction of 31.3 min/day of sedentary behavior at 12 months, versus being isolated [95% CI: (−61.4, −1.07), p = 0.04]. Certain social network conditions may make it easier to reduce adult sedentary behavior in group-based interventions. While further research will be necessary to establish causality, the implications for intervention design are discussed.

scholarly journals Differences in anxieties and social networks in a group-matched sample of autistic and typically developing students transitioning to university

Autism ◽  
2019 ◽  
Vol 24 (5) ◽  
pp. 1138-1151
Author(s):  
Jiedi Lei ◽  
Chris Ashwin ◽  
Mark Brosnan ◽  
Ailsa Russell
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Anxiety ◽  
Autistic Traits ◽  
Network Size ◽  
Typically Developing ◽  
Social Network Size ◽  
Social Network Structure ◽  
Matched Design ◽  
The Relationship

Transitioning to university can be anxiety-provoking for all students. The relationship between social anxiety, autistic traits and students’ social network structure, and perceived support is poorly understood. This study used a group-matched design where autistic students ( n = 28) and typically developing students ( n = 28) were matched on sex, age (17–19 years), ethnicity, pre-university academic performance and degree subject at university. Autistic students reported greater transition to university worries, and a smaller social network size compared to typically developing students, though perceived similar levels of support from their social networks. Autistic and typically developing students showed differential patterns of association with both autistic traits and social anxiety. Broader clinical and practical implications of findings are discussed.

scholarly journals Interactions with humans are jointly influenced by life history stage and social network factors and reduce group cohesion in moor macaques (Macaca maura)

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kristen S. Morrow ◽  
Hunter Glanz ◽  
Putu Oka Ngakan ◽  
Erin P. Riley
Keyword(s):  
Social Networks ◽  
Life History ◽  
Social Network ◽  
Interindividual Variation ◽  
Life History Stage ◽  
The Road ◽  
Network Position ◽  
Moor Macaques ◽  
Structure Changes ◽  
Social Network Structure

AbstractHuman-wildlife encounters are becoming increasingly frequent across the globe, often leading people to interact with and feed wild animals and impacting animal behaviour and ecology. Although the nature of human-wildlife interactions has been well documented across a number of species, we still have limited understanding as to why some individual animals interact more frequently with humans than others. Additionally, we lack a comprehensive understanding of how these interactions influence animal social networks. Using behavioural data from a group of moor macaque monkeys (Macaca maura), we used permutation-based linear regression analyses to understand how life history and social network factors jointly explain interindividual variation in tendency to interact with humans along a provincial road in South Sulawesi, Indonesia. As our study group spent only a portion of their time in proximity to humans, we also examined how social network structure changes in response to human presence by comparing social networks in the forest to those along the road. We found that sex, individual network position, and associate network position interact in complex ways to influence individual behaviour. Individual variation in tendency to be along the road caused social networks to become less cohesive when in proximity to humans. This study demonstrates that nuanced intragroup analyses are necessary to fully understand and address conservation issues relating to human-wildlife interactions.

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