The influence of demographic variation on social network stability in wild vervet monkeys

2017 ◽  
Vol 134 ◽  
pp. 155-165 ◽  
Author(s):  
Christèle Borgeaud ◽  
Sebastian Sosa ◽  
Cédric Sueur ◽  
Redouan Bshary
Keyword(s):  
Social Network ◽  
Vervet Monkeys ◽  
Network Stability ◽  
Demographic Variation

scholarly journals Analysis of The Utilization of the Social Center for Orangutan Protection (COP) In Kalimantan in Orangutan Saving Efforts

2020 ◽  
Vol 1 (1) ◽  
pp. 9-17
Author(s):  
Octalina Hardiyanti ◽  
Agustin Nurmanina
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Human Resources ◽  
The Other ◽  
Weak Ties ◽  
Power Networks ◽  
Network Stability ◽  
Work Patterns ◽  
The Social ◽  
Local Actors

ABSTRACT: Utilization of the Center for Orangutan Protection (COP) 2 social network in Kalimantan. With the limited number of human resources compared to the wide scope of work in all of Kalimantan, COP makes use of its social networks to meet the needs and the functioning of the organization. In investigative activities, COP has effectively used weak ties to obtain information on the whereabouts of orangutans and the destruction of their habitat. The policies in this activity are also dominated by central actors through their power networks which result in network stability. In contrast to the use of social networks for educational activities, local actors are more dominant in making program policies and work patterns. In the alternation between actors from time to time, there are differences in assumptions and work patterns of the actors in charge, resulting in differences in utilization results and potential network damage. COP can utilize its social network in fulfilling its function as an NGO campaigning for the protection and rescue of orangutans, but on the other hand, COP's bonding social network only connects this NGO with similar organizations, limited to handling cases of orangutans and their habitat. Supporting nature conservation, such as economic, social, and cultural, as part of the needs of the community around the ring habitat is not fulfilled. ABSTRAK: Pemanfaatan jaringan sosial Centre for Orangutan Protection (COP)2 di Kalimantan. Dengan keterbatasan jumlah SDM dibanding luasnya cakupan kerja di seluruh Kalimantan, COP memanfaatkan jaringan sosialnya untuk memenuhi kebutuhan dan berjalannya fungsi organisasi. Dalam kegiatan investigasi COP efektif menggunakan ikatan lemah untuk memperoleh informasi keberadaan orangutan dan perusakan habitatnya. Kebijakan dalam aktivitas ini pun didominasi aktor pusat melalui jaringan powernya yang menghasilkan stabilitas jaringan. Berbeda dengan pemanfaatan jaringan sosial untuk kegiatan edukasi, aktor lokal lebih dominan mengambil kebijakan program dan pola kerja. Dalam pergantian antar aktor pada masa ke masa terdapat perbedaan asumsi dan pola kerja aktor-aktor yang bertugas sehingga menimbulkan perbedaan hasil pemanfaatan hingga potensi terjadinya kerusakan jaringan. COP mampu memanfaatkan jaringan sosialnya dalam memenuhi fungsinya sebagai LSM yang mengkampanyekan perlindungan dan penyelamatan orangutan, namun sisi lainnya jaringan sosial COP yang bersifat bonding (tertutup) hanya menghubungkan LSM ini dengan organisasi sejenis terbatas pada penanganan kasus orangutan dan habitatnya. Pendukung konservasi alam seperti ekonomi, sosial dan budaya sebagai bagian dari kebutuhan masyarakat di sekitar ring habitat tak terpenuhi.

Social network stability is impacted by removing a dominant male in replicate dominance hierarchies of a cichlid fish

2021 ◽  
Vol 175 ◽  
pp. 7-20
Author(s):  
Taylor J. Piefke ◽  
Tyler R. Bonnell ◽  
Gabriela M. DeOliveira ◽  
Shana E. Border ◽  
Peter D. Dijkstra
Keyword(s):  
Social Network ◽  
Cichlid Fish ◽  
Dominant Male ◽  
Network Stability ◽  
Dominance Hierarchies

scholarly journals Evaluating transdisciplinary research practices: insights from social network analysis

2021 ◽  
Author(s):  
T. Steelman ◽  
◽  
A. Bogdan ◽  
C. Mantyka-Pringle ◽  
L. Bradford ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Result ◽  
Transdisciplinary Research ◽  
Network Stability ◽  
Research Activity ◽  
Performance Expectations ◽  
Sustainability Problems ◽  
Patterns Of Interaction

AbstractTransdisciplinary researchers collaborate with diverse partners outside of academia to tackle sustainability problems. The patterns and practices of social interaction and the contextual nature of transdisciplinary research result in different performance expectations than traditional, curiosity-driven research. Documenting patterns of interaction can inform project success and affirm progress toward interim outcomes on the way to achieve sustainability impacts. Yet providing credible and robust indicators of research activity remains challenging. We provide quantitative and qualitative indicators for assessing transdisciplinary practices and patterns through social network analysis (SNA). Our assessment developed four criteria to reveal how SNA metrics provide insight into (1) diversity of participants; (2) whether and how integration and collaboration are occurring, (3) the relative degrees of network stability and fragility, and (4) how the network is structured to achieve its goals. These four key criteria can be used to help identify patterns of research activity and determine whether interim progress is occurring.

scholarly journals Reciprocity and behavioral heterogeneity govern the stability of social networks

2019 ◽  
Author(s):  
Roslyn Dakin ◽  
T. Brandt Ryder
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Simple Model ◽  
Social Systems ◽  
Bird Species ◽  
Social Stability ◽  
Network Stability ◽  
Trade Off ◽  
The Social ◽  
Behavioral Heterogeneity

AbstractThe dynamics of social networks can determine the transmission of information, the spread of diseases, and the evolution of behavior. Despite this broad importance, a general framework for predicting social network stability has not been proposed. Here, we present longitudinal data on the social dynamics of a cooperative bird species, the wire-tailed manakin, to evaluate the potential causes of temporal network stability. We find that when partners interact less frequently, and when the breadth of social connectedness within the network increases, the social network is subsequently less stable. Social connectivity was also negatively associated with the temporal persistence of coalition partnerships on an annual timescale. This negative association between connectivity and stability was surprising, especially given that individual manakins who were more connected also had more stable partnerships. This apparent paradox arises from a within-individual behavioral trade-off between partnership quantity and quality. Crucially, this trade-off is easily masked by behavioral variation among individuals. Using a simulation, we show that these results are explained by a simple model that combines among-individual behavioral heterogeneity and reciprocity within the network. As social networks become more connected, individuals face a trade-off between partnership quantity and maintenance. This model also demonstrates how among-individual behavioral heterogeneity, a ubiquitous feature of natural societies, can improve social stability. Together, these findings provide unifying principles that are expected to govern diverse social systems.Significance StatementIn animal societies, social partnerships form a dynamic network that can change over time. Why are some social network structures more stable than others? We addressed this question by studying a cooperative bird species in which social behavior is important for fitness, similar to humans. We found that stable social networks are characterized by more frequent interactions, but sparser connectivity throughout the network. Using a simulation, we show how both results can be explained by a simple model of reciprocity. These findings indicate that social stability is governed by a trade-off whereby individuals can either maintain a few high-quality partners, or increase partner number. This fundamental trade-off may govern the dynamics and stability of many societies, including in humans.

The social network

2013 ◽  
Vol 44 (2) ◽  
pp. 22
Author(s):  
ALAN ROCKOFF
Keyword(s):  
Social Network ◽  
The Social

Abstract #1249: Novel Use of Physician Social Network Data to Map the Gap in the Endocrinology Workforce

2015 ◽  
Vol 21 ◽  
pp. 301
Author(s):  
Armand Krikorian ◽  
Lily Peng ◽  
Zubair Ilyas ◽  
Joumana Chaiban
Keyword(s):  
Social Network ◽  
Network Data ◽  
Social Network Data

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

Extraverts Have Larger Social Network Layers

2011 ◽  
Vol 32 (3) ◽  
pp. 161-169 ◽  
Author(s):  
Thomas V. Pollet ◽  
Sam G. B. Roberts ◽  
Robin I. M. Dunbar
Keyword(s):  
Social Network ◽  
Social Relationships ◽  
Outer Layer ◽  
Network Size ◽  
Emotional Intensity ◽  
Emotional Closeness ◽  
Network Layer ◽  
Network Layers ◽  
Social Network Size

Previous studies showed that extraversion influences social network size. However, it is unclear how extraversion affects the size of different layers of the network, and how extraversion relates to the emotional intensity of social relationships. We examined the relationships between extraversion, network size, and emotional closeness for 117 individuals. The results demonstrated that extraverts had larger networks at every layer (support clique, sympathy group, outer layer). The results were robust and were not attributable to potential confounds such as sex, though they were modest in size (raw correlations between extraversion and size of network layer, .20 < r < .23). However, extraverts were not emotionally closer to individuals in their network, even after controlling for network size. These results highlight the importance of considering not just social network size in relation to personality, but also the quality of relationships with network members.

The Multilevel p2 Model

Methodology ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 42-47 ◽  
Author(s):  
Bonne J. H. Zijlstra ◽  
Marijtje A. J. van Duijn ◽  
Tom A. B. Snijders
Keyword(s):  
Social Network ◽  
Network Data ◽  
Mcmc Algorithm ◽  
Independent Observation ◽  
Single Observation ◽  
Multiple Networks ◽  
Social Network Data ◽  
Multiple Observations ◽  
Practical Support ◽  
The Social

The p 2 model is a random effects model with covariates for the analysis of binary directed social network data coming from a single observation of a social network. Here, a multilevel variant of the p 2 model is proposed for the case of multiple observations of social networks, for example, in a sample of schools. The multilevel p 2 model defines an identical p 2 model for each independent observation of the social network, where parameters are allowed to vary across the multiple networks. The multilevel p 2 model is estimated with a Bayesian Markov Chain Monte Carlo (MCMC) algorithm that was implemented in free software for the statistical analysis of complete social network data, called StOCNET. The new model is illustrated with a study on the received practical support by Dutch high school pupils of different ethnic backgrounds.

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