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.

scholarly journals Polarized information ecosystems can reorganize social networks via information cascades

2021 ◽  
Vol 118 (50) ◽  
pp. e2102147118 ◽  
Author(s):  
Christopher K. Tokita ◽  
Andrew M. Guess ◽  
Corina E. Tarnita
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Computational Model ◽  
Network Structure ◽  
Information Sources ◽  
Social Ties ◽  
Network Data ◽  
Information Cascades ◽  
Structure Changes ◽  
Social Network Structure

The precise mechanisms by which the information ecosystem polarizes society remain elusive. Focusing on political sorting in networks, we develop a computational model that examines how social network structure changes when individuals participate in information cascades, evaluate their behavior, and potentially rewire their connections to others as a result. Individuals follow proattitudinal information sources but are more likely to first hear and react to news shared by their social ties and only later evaluate these reactions by direct reference to the coverage of their preferred source. Reactions to news spread through the network via a complex contagion. Following a cascade, individuals who determine that their participation was driven by a subjectively “unimportant” story adjust their social ties to avoid being misled in the future. In our model, this dynamic leads social networks to politically sort when news outlets differentially report on the same topic, even when individuals do not know others’ political identities. Observational follow network data collected on Twitter support this prediction: We find that individuals in more polarized information ecosystems lose cross-ideology social ties at a rate that is higher than predicted by chance. Importantly, our model reveals that these emergent polarized networks are less efficient at diffusing information: Individuals avoid what they believe to be “unimportant” news at the expense of missing out on subjectively “important” news far more frequently. This suggests that “echo chambers”—to the extent that they exist—may not echo so much as silence.

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 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 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.

NETWORK NOT UTILIZED: THE CASE OF ULTRA-ORTHODOX FEMALE MICRO-ENTREPRENEURS IN ISRAEL

2016 ◽  
Vol 21 (01) ◽  
pp. 1650006 ◽  
Author(s):  
YISCA MONNICKENDAM-GIVON ◽  
DAFNA SCHWARTZ ◽  
BENJAMIN GIDRON
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Size ◽  
Policy Implications ◽  
Entrepreneurial Success ◽  
Successful Management ◽  
Social Network Structure ◽  
Size Number ◽  
Salient Factor

The study examines the role of social networks in the Ultra-Orthodox community in Israel as a tool for promoting micro-entrepreneurial success. To date, research has shown that social network structure is a salient factor in the successful management of micro-businesses. We explored network size, number of strong, weak and betweenness ties of Ultra-Orthodox female micro-entrepreneurs, a distinct social-religious enclave that remains largely unexplored. Contrary to literature, our findings show that Ultra-Orthodox female micro-entrepreneurs have a narrow network in all parameters explored. Although they have a far-reaching social network, it is virtually unutilized in promoting their micro-businesses. Theoretical and policy implications are discussed.

scholarly journals Social Network Structure Is Related to Functional Improvement From Home-Based Telerehabilitation After Stroke

2021 ◽  
Vol 12 ◽  
Author(s):  
Archana Podury ◽  
Sophia M. Raefsky ◽  
Lucy Dodakian ◽  
Liam McCafferty ◽  
Vu Le ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Depressive Symptoms ◽  
Network Structure ◽  
Network Size ◽  
Network Density ◽  
Stroke Patients ◽  
Historical Cohort ◽  
Home Based ◽  
Social Network Structure

Objective: Telerehabilitation (TR) is now, in the context of COVID-19, more clinically relevant than ever as a major source of outpatient care. The social network of a patient is a critical yet understudied factor in the success of TR that may influence both engagement in therapy programs and post-stroke outcomes. We designed a 12-week home-based TR program for stroke patients and evaluated which social factors might be related to motor gains and reduced depressive symptoms.Methods: Stroke patients (n = 13) with arm motor deficits underwent supervised home-based TR for 12 weeks with routine assessments of motor function and mood. At the 6-week midpoint, we mapped each patient's personal social network and evaluated relationships between social network metrics and functional improvements from TR. Finally, we compared social networks of TR patients with a historical cohort of 176 stroke patients who did not receive any TR to identify social network differences.Results: Both network size and network density were related to walk time improvement (p = 0.025; p = 0.003). Social network density was related to arm motor gains (p = 0.003). Social network size was related to reduced depressive symptoms (p = 0.015). TR patient networks were larger (p = 0.012) and less dense (p = 0.046) than historical stroke control networks.Conclusions: Social network structure is positively related to improvement in motor status and mood from TR. TR patients had larger and more open social networks than stroke patients who did not receive TR. Understanding how social networks intersect with TR outcomes is crucial to maximize effects of virtual rehabilitation.

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