scholarly journals Do zealots increase or decrease the polarization of social networks?

2019 ◽  
Vol 8 (4) ◽  
Author(s):  
Snehal M Shekatkar
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Majority Rule ◽  
Initial Conditions ◽  
Opinion Dynamics ◽  
Network Density ◽  
Configuration Model ◽  
Rule Model ◽  
Total Fraction ◽  
Topological Characteristics

Abstract Zealots are the vertices in a social network who do not change their opinions under social pressure and are crucial to the study of opinion dynamics on complex networks. In this article, we study the effect of zealots on the polarization dynamics of a deterministic majority rule model using the configuration model as a substrate. To this end, we propose a novel quantifier, called ‘correlated polarization’, for measuring the amount of polarization in the network when vertices can exist in two opposite states. The quantifier takes into account not only the fraction of vertices with each opinion but also how they are connected to each other. We then show that the presence of zealots does not have a fixed effect on the polarization, and can change it in positive, negative or neutral way depending upon their topological characteristics like degree, their total fraction in the network, density and degree heterogeneity of the network and the type of initial conditions of the dynamics. Our results particularly highlight the importance of the role played by the initial conditions in drifting the polarization towards lower or higher values as the total number of zealots is increased.

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.

Supporting political violence: The role of ideological passion and social network

2020 ◽  
Vol 23 (8) ◽  
pp. 1187-1203
Author(s):  
Jocelyn J. Bélanger ◽  
Blaine G. Robbins ◽  
Hayat Muhammad ◽  
Manuel Moyano ◽  
Claudia F. Nisa ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Political Violence ◽  
Group Processes ◽  
Network Density ◽  
Harmonious Passion ◽  
Cultural Contexts ◽  
Analysis Study ◽  
Insight Into

This research examines how social networks contribute to the process of radicalization, building on work showing that obsessive (vs. harmonious) passion for a cause is linked to greater support for political violence. Study 1 ( N = 331) shows that obsessive (vs. harmonious) passion is related to affiliating with radical (vs. moderate) social networks, which in turn is associated with support for political violence. Study 2 ( N = 381) provides experimental evidence for this phenomenon, by showing that inducing an obsessive mindset produces a greater proclivity to connect with radical activists, which in turn is associated with greater support for political violence. Drawing from social network analysis, Study 3 ( N = 366) shows that network density intensifies obsessively passionate individuals’ affiliation to radical networks. The results offer insight into the group processes behind radicalization across different cultural contexts and ideologies.

scholarly journals Trust and manipulation in social networks

2016 ◽  
Vol 4 (2) ◽  
pp. 216-243 ◽  
Author(s):  
MANUEL FÖRSTER ◽  
ANA MAULEON ◽  
VINCENT J. VANNETELBOSCH
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Opinion Dynamics ◽  
Information Aggregation ◽  
Common Interest ◽  
Opinion Leadership ◽  
Weighted Averages

AbstractWe investigate the role of manipulation in boundedly rational opinion dynamics. Agents are subject to persuasion bias and repeatedly communicate with their neighbors in a social network. They can exert effort to manipulate trust in the opinions of others in their favor and update their opinions about some issue of common interest by taking weighted averages of neighbors' opinions. We show that manipulation can connect a segregated society and thus lead to mutual consensus. Second, we show that manipulation fosters opinion leadership; and surprisingly agents with low trust in their own opinion might get more influential even by being manipulated. Finally, comparative simulations reveal that manipulation is beneficial to information aggregation when preferences and abilities for manipulation are homogeneous, but detrimental in case abilities are concentrated at few powerful agents.

Phase transition and universality of the three-one spin interaction based on the majority-rule model

2021 ◽  
pp. 2150115
Author(s):  
Roni Muslim ◽  
Rinto Anugraha ◽  
Sholihun Sholihun ◽  
Muhammad Farchani Rosyid
Keyword(s):  
Phase Transition ◽  
Critical Point ◽  
Majority Rule ◽  
Mean Field ◽  
Opinion Dynamics ◽  
Universality Class ◽  
Spin Interaction ◽  
Population Number ◽  
Infinite Population ◽  
Rule Model

In this work, we study the opinion dynamics of majority-rule model on a complete graph with additional social behavior namely anticonformity. We consider four spins with three-one interaction; three spins persuade the fourth spin in the population. We perform analytical and numerical calculations to find the critical behavior of the system. From both, we obtained the agreement results, e.g. the system undergoes a second-order phase transition and the critical point of the system only depends on the population number. In addition, the critical point decays exponentially as the number population increases. For the infinite population, the obtained critical point is [Formula: see text], which agrees well with that of the previous work. We also obtained the critical exponents [Formula: see text] and [Formula: see text] of the model, thus, the model is in the same universality class with the mean-field Ising.

scholarly journals Using Social Network Analysis to Identify Key Child Care Center Staff for Obesity Prevention Interventions: A Pilot Study

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Jennifer Marks ◽  
Lisa M. Barnett ◽  
Chad Foulkes ◽  
Penelope Hawe ◽  
Steven Allender
Keyword(s):  
Physical Activity ◽  
Social Networks ◽  
Social Network ◽  
Obesity Prevention ◽  
Day Care ◽  
Care Center ◽  
Network Density ◽  
Day Care Centers ◽  
Center Staff ◽  
Long Day

Introduction. Interest has grown in how systems thinking could be used in obesity prevention. Relationships between key actors, represented by social networks, are an important focus for considering intervention in systems.Method. Two long day care centers were selected in which previous obesity prevention programs had been implemented. Measures showed ways in which physical activity and dietary policy are conversations and actions transacted through social networks (interrelationships) within centers, via an eight item closed-ended social network questionnaire. Questionnaire data were collected from (17/20; response rate 85%) long day care center staff. Social network density and centrality statistics were calculated, using UCINET social network software, to examine the role of networks in obesity prevention.Results. “Degree” (influence) and “betweeness” (gatekeeper) centrality measures of staff inter-relationships about physical activity, dietary, and policy information identified key players in each center. Network density was similar and high on some relationship networks in both centers but markedly different in others, suggesting that the network tool identified unique center social dynamics. These differences could potentially be the focus of future team capacity building.Conclusion. Social network analysis is a feasible and useful method to identify existing obesity prevention networks and key personnel in long day care centers.

scholarly journals Voter and Majority Dynamics with Biased and Stubborn Agents

2020 ◽  
Vol 181 (4) ◽  
pp. 1239-1265
Author(s):  
Arpan Mukhopadhyay ◽  
Ravi R. Mazumdar ◽  
Rahul Roy
Keyword(s):  
Majority Rule ◽  
Branching Processes ◽  
Mean Field ◽  
Opinion Dynamics ◽  
Majority Opinion ◽  
Rule Model ◽  
Interacting Agents ◽  
The Mean ◽  
Fully Connected ◽  
Mean Time

Abstract We study binary opinion dynamics in a fully connected network of interacting agents. The agents are assumed to interact according to one of the following rules: (1) Voter rule: An updating agent simply copies the opinion of another randomly sampled agent; (2) Majority rule: An updating agent samples multiple agents and adopts the majority opinion in the selected group. We focus on the scenario where the agents are biased towards one of the opinions called the preferred opinion. Using suitably constructed branching processes, we show that under both rules the mean time to reach consensus is $$\varTheta (\log N)$$ Θ ( log N ) , where N is the number of agents in the network. Furthermore, under the majority rule model, we show that consensus can be achieved on the preferred opinion with high probability even if it is initially the opinion of the minority. We also study the majority rule model when stubborn agents with fixed opinions are present. We find that the stationary distribution of opinions in the network in the large system limit using mean field techniques.

scholarly journals Reconfiguration and Search of Social Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-11
Author(s):  
Lianming Zhang ◽  
Aoyuan Peng ◽  
Jianping Yu
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Clustering Coefficient ◽  
Node Degree ◽  
Hybrid Search ◽  
The Social ◽  
Search Speed ◽  
Topological Characteristics ◽  
Regular Networks ◽  
High Degree

Social networks tend to exhibit some topological characteristics different from regular networks and random networks, such as shorter average path length and higher clustering coefficient, and the node degree of the majority of social networks obeys exponential distribution. Based on the topological characteristics of the real social networks, a new network model which suits to portray the structure of social networks was proposed, and the characteristic parameters of the model were calculated. To find out the relationship between two people in the social network, and using the local information of the social network and the parallel mechanism, a hybrid search strategy based onk-walker random and a high degree was proposed. Simulation results show that the strategy can significantly reduce the average number of search steps, so as to effectively improve the search speed and efficiency.

scholarly journals Detecting Bots and Assessing Their Impact in Social Networks

2021 ◽  
Author(s):  
Nicolas Guenon des Mesnards ◽  
David Scott Hunter ◽  
Zakaria el Hjouji ◽  
Tauhid Zaman
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Statistical Physics ◽  
Opinion Dynamics ◽  
Data Sets ◽  
Social Network Data ◽  
Operational Capabilities ◽  
Dynamics Models ◽  
The Impact ◽  
The U.S

Bots Impact Opinions in Social Networks: Let’s Measure How Much There is a serious threat posed by bots that try to manipulate opinions in social networks. In “Assessing the Impact of Bots on Social Networks,” Nicolas Guenon des Mesnards, David Scott Hunter, Zakaria el Hjouiji, and Tauhid Zaman present a new set of operational capabilities to detect these bots and measure their impact. They developed an algorithm based on the Ising model from statistical physics to find coordinating gangs of bots in social networks. They then created an algorithm based on opinion dynamics models to quantify the impact that bots have on opinions in a social network. They applied their algorithms to a variety of real social network data sets. They found that, for topics such as Brexit, the bots had little impact, whereas for topics such as the U.S. presidential debate and the Gilets Jaunes protests in France, the bots had a significant impact.

Reasoning about opinion dynamics in social networks

2015 ◽  
Vol 29 (7) ◽  
pp. 1121-1137 ◽  
Author(s):  
Jens Ulrik Hansen
Keyword(s):  
Social Networks ◽  
Fuzzy Logic ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Opinion Dynamics ◽  
Hybrid Logic ◽  
Modal Operators ◽  
Mathematical Properties

Abstract This article introduces a logic to reason about a well-known model of opinion dynamics in social networks initially developed by Morris DeGroot as well as Keith Lehrer and Carl Wagner. The proposed logic is an extension of Łukasiewicz' fuzzy logic with additional equational expressivity, modal operators, machinery from hybrid logic and dynamic modalities. The model of opinion dynamics in social networks is simple enough to be easily grasped, but still complex enough to have interesting mathematical properties and applications. Thus, developing a logic to reason about this particular model serves as a paradigmatic example of how logic can be useful in social network analysis.

Majority rule dynamics between a double coalition and a third opinion: coalition profit models and majority coalition ties

2020 ◽  
pp. 105971231989548
Author(s):  
Felipe Gayosso Martínez ◽  
Alexander Balankin
Keyword(s):  
Majority Rule ◽  
Social Dynamics ◽  
Opinion Dynamics ◽  
Network Size ◽  
Opinion Formation ◽  
Random Choice ◽  
Rule Model ◽  
Rule Dynamics ◽  
Lattice Network ◽  
Consensus Time

This article explores the opinion dynamics of a double coalition opinion against a third opinion under majority rule updates on odd fixed size connected groups. For this purpose, coalition benefit criteria and three opinion formation models which extend the 2-state majority rule model on lattices are introduced. The proposed models focus on the coalition profit of its constituent coalition opinions and cover the possible final scenarios from coalition alliance perspective: either minor opinion or major opinion is favored, or dynamics do not favor to any coalition opinion. Opinion exchanges take place on a torus embedded lattice network of a 3-state system having in consideration tie configurations and two rules to break them: either by random choice or leaving ties unaltered. Models were analyzed in the statistical mechanics spirit through Monte Carlo simulations without node replacement. Estimations for coalition benefits, the growth of coalition ties, and consensus probabilities are reported. The loss of coalition strengths due to coalition ties and its indecision is indicated. In particular, the logistic decay of consensus probability is due to the logistic adaptive growth of coalition ties. Scaling behaviors for consensus time and coalition ties in terms of network size are suggested. The results of numerical simulations are discussed in the context of social influence and social dynamics.

Sign in / Sign up

Export Citation Format

Share Document