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.

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

2020 ◽  
Vol 117 (6) ◽  
pp. 2993-2999 ◽  
Author(s):  
Roslyn Dakin ◽  
T. Brandt Ryder
Keyword(s):  
Social Networks ◽  
Social Connectedness ◽  
Social Dynamics ◽  
Social Systems ◽  
Bird Species ◽  
Network Stability ◽  
Apparent Paradox ◽  
Trade Off ◽  
Behavioral Heterogeneity ◽  
The Stability

The 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 social connectedness increases, the 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.

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.

scholarly journals Social inheritance can explain the structure of animal social networks

2015 ◽  
Author(s):  
Amiyaal Ilany ◽  
Erol Akcay
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Structure ◽  
Social Systems ◽  
Null Model ◽  
Pathogen Transmission ◽  
Social Network Structure ◽  
Animal Populations ◽  
The Social ◽  
Specific Factors

AbstractThe social network structure of animal populations has major implications for survival, reproductive success, sexual selection, and pathogen transmission of individuals. But as of yet, no general theory of social network structure exists that can explain the diversity of social networks observed in nature, and serve as a null model for detecting species and population-specific factors. Here we propose a simple and generally applicable model of social network structure. We consider the emergence of network structure as a result of social inheritance, in which newborns are likely to bond with maternal contacts, and via forming bonds randomly. We compare model output to data from several species, showing that it can generate networks with properties such as those observed in real social systems. Our model demonstrates that important observed properties of social networks, including heritability of network position or assortative associations, can be understood as consequences of social inheritance.

Emotive Trending And Tracking of Tweets

2017 ◽  
Vol 7 (11) ◽  
pp. 25
Author(s):  
Sanjay Chhataru Gupta
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
The Social ◽  
The World ◽  
Complex Events

Popularity of the social media and the amount of importance given by an individual to social media has significantly increased in last few years. As more and more people become part of the social networks like Twitter, Facebook, information which flows through the social network, can potentially give us good understanding about what is happening around in our locality, state, nation or even in the world. The conceptual motive behind the project is to develop a system which analyses about a topic searched on Twitter. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. The system tracks changes in emotions over events, signalling possible flashpoints or abatement. For each trending topic, the system also shows a sentiment graph showing how positive and negative sentiments are trending as the topic is getting trended.

The Oxford Handbook of Social Networks

2020 ◽  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Life ◽  
Information Science ◽  
Computational Social Science ◽  
The Social ◽  
Diverse Field ◽  
The Rich

Social networks fundamentally shape our lives. Networks channel the ways that information, emotions, and diseases flow through populations. Networks reflect differences in power and status in settings ranging from small peer groups to international relations across the globe. Network tools even provide insights into the ways that concepts, ideas and other socially generated contents shape culture and meaning. As such, the rich and diverse field of social network analysis has emerged as a central tool across the social sciences. This Handbook provides an overview of the theory, methods, and substantive contributions of this field. The thirty-three chapters move through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. The Handbook includes chapters on data collection and visualization, theoretical innovations, links between networks and computational social science, and how social network analysis has contributed substantively across numerous fields. As networks are everywhere in social life, the field is inherently interdisciplinary and this Handbook includes contributions from leading scholars in sociology, archaeology, economics, statistics, and information science among others.

Comparing the social networks of service users with long term mental health needs living in community with those in a general adult in-patient unit

2021 ◽  
pp. 002076402110175
Author(s):  
Roberto Rusca ◽  
Ike-Foster Onwuchekwa ◽  
Catherine Kinane ◽  
Douglas MacInnes
Keyword(s):  
Mental Health ◽  
Social Networks ◽  
Social Network ◽  
Patient Group ◽  
Mental Health Problems ◽  
Well Being ◽  
Health Problems ◽  
Practical Support ◽  
The Social

Background: Relationships are vital to recovery however, there is uncertainty whether users have different types of social networks in different mental health settings and how these networks may impact on users’ wellbeing. Aims: To compare the social networks of people with long-term mental illness in the community with those of people in a general adult in-patient unit. Method: A sample of general adult in-patients with enduring mental health problems, aged between 18 and 65, was compared with a similar sample attending a general adult psychiatric clinic. A cross-sectional survey collected demographic data and information about participants’ social networks. Participants also completed the Short Warwick Edinburgh Mental Well-Being Scale to examine well-being and the Significant Others Scale to explore their social network support. Results: The study recruited 53 participants (25 living in the community and 28 current in-patients) with 339 named as important members of their social networks. Both groups recorded low numbers in their social networks though the community sample had a significantly greater number of social contacts (7.4 vs. 5.4), more monthly contacts with members of their network and significantly higher levels of social media use. The in-patient group reported greater levels of emotional and practical support from their network. Conclusions: People with serious and enduring mental health problems living in the community had a significantly greater number of people in their social network than those who were in-patients while the in-patient group reported greater levels of emotional and practical support from their network. Recommendations for future work have been made.

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.

Social Networks, Their Basic Factors, as Well as Their Role in Society and the State in the Context of Digital Transformation

2020 ◽  
Vol 144 ◽  
pp. 26-35
Author(s):  
Rem V. Ryzhov ◽  
◽  
Vladimir A. Ryzhov ◽  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Life Support ◽  
Social Institutions ◽  
The State ◽  
Main Task ◽  
Organizational Models ◽  
Control Center ◽  
The Social ◽  
Single Strategy

Society is historically associated with the state, which plays the role of an institution of power and government. The main task of the state is life support, survival, development of society and the sovereignty of the country. The main mechanism that the state uses to implement these functions is natural social networks. They permeate every cell of society, all elements of the country and its territory. However, they can have a control center, or act on the principle of self-organization (network centrism). The web is a universal natural technology with a category status in science. The work describes five basic factors of any social network, in particular the state, as well as what distinguishes the social network from other organizational models of society. Social networks of the state rely on communication, transport and other networks of the country, being a mechanism for the implementation of a single strategy and plan. However, the emergence of other strong network centers of competition for state power inevitably leads to problems — social conflicts and even catastrophes in society due to the destruction of existing social institutions. The paper identifies the main pitfalls using alternative social networks that destroy the foundations of the state and other social institutions, which leads to the loss of sovereignty, and even to the complete collapse of the country.

Factors Affecting Individual Level ERP Assimilation in a Social Network Perspective

2017 ◽  
Vol 25 (3) ◽  
pp. 21-39 ◽  
Author(s):  
Luan Gao ◽  
Luning Liu ◽  
Yuqiang Feng
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Interactive Learning ◽  
Influential Factors ◽  
Three Dimensions ◽  
Organizational Level ◽  
Key Factors ◽  
Factors Affecting ◽  
Individual Level ◽  
The Social

Prior research on ERP assimilation has primarily focused on influential factors at the organizational level. In this study, the authors attempt to extend their understanding of individual level ERP assimilation from the perspective of social network theory. They designed a multi-case study to explore the relations between ERP users' social networks and their levels of ERP assimilation based on the three dimensions of the social networks. The authors gathered data through interviews with 26 ERP users at different levels in five companies. Qualitative analysis was used to understand the effects of social networks and interactive learning. They found that users' social networks play a significant role in individual level ERP assimilation through interactive learning among users. They also found five key factors that facilitate users' assimilation of ERP knowledge: homophily (age, position and rank), tie content (instrumental and expressive ties), tie strength, external ties, and centrality.

scholarly journals Research on Sentiment Tendency and Evolution of Public Opinions in Social Networks of Smart City

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Yanni Liu ◽  
Dongsheng Liu ◽  
Yuwei Chen
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Sentiment Analysis ◽  
Smart City ◽  
Topic Model ◽  
Rapid Development ◽  
Mobile Internet ◽  
Time Curve ◽  
Public Opinions ◽  
The Social

With the rapid development of mobile Internet, the social network has become an important platform for users to receive, release, and disseminate information. In order to get more valuable information and implement effective supervision on public opinions, it is necessary to study the public opinions, sentiment tendency, and the evolution of the hot events in social networks of a smart city. In view of social networks’ characteristics such as short text, rich topics, diverse sentiments, and timeliness, this paper conducts text modeling with words co-occurrence based on the topic model. Besides, the sentiment computing and the time factor are incorporated to construct the dynamic topic-sentiment mixture model (TSTS). Then, four hot events were randomly selected from the microblog as datasets to evaluate the TSTS model in terms of topic feature extraction, sentiment analysis, and time change. The results show that the TSTS model is better than the traditional models in topic extraction and sentiment analysis. Meanwhile, by fitting the time curve of hot events, the change rules of comments in the social network is obtained.

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