scholarly journals Cumulative effects of triadic closure and homophily in social networks

2020 ◽  
Vol 6 (19) ◽  
pp. eaax7310 ◽  
Author(s):  
Aili Asikainen ◽  
Gerardo Iñiguez ◽  
Javier Ureña-Carrión ◽  
Kimmo Kaski ◽  
Mikko Kivelä
Keyword(s):  
Social Networks ◽  
Communication Networks ◽  
Empirical Studies ◽  
Network Evolution ◽  
Cumulative Effects ◽  
Small Individual ◽  
Individual Level ◽  
Social Network Structure ◽  
Triadic Closure ◽  
Dynamic Interplay

Social network structure has often been attributed to two network evolution mechanisms—triadic closure and choice homophily—which are commonly considered independently or with static models. However, empirical studies suggest that their dynamic interplay generates the observed homophily of real-world social networks. By combining these mechanisms in a dynamic model, we confirm the longheld hypothesis that choice homophily and triadic closure cause induced homophily. We estimate how much observed homophily in friendship and communication networks is amplified due to triadic closure. We find that cumulative effects of homophily amplification can also lead to the widely documented core-periphery structure of networks, and to memory of homophilic constraints (equivalent to hysteresis in physics). The model shows that even small individual bias may prompt network-level changes such as segregation or core group dominance. Our results highlight that individual-level mechanisms should not be analyzed separately without considering the dynamics of society as a whole.

scholarly journals Collective communication and behaviour in response to uncertain ‘Danger’ in network experiments

2020 ◽  
Vol 476 (2237) ◽  
pp. 20190685
Author(s):  
Hirokazu Shirado ◽  
Forrest W. Crawford ◽  
Nicholas A. Christakis
Keyword(s):  
Social Networks ◽  
Interpersonal Communication ◽  
Communication Networks ◽  
Social Information ◽  
Collective Communication ◽  
Group Topology ◽  
Individual Level ◽  
Social Coordination ◽  
The Individual ◽  
Actual Accuracy

In emergencies, social coordination is especially challenging. People connected with each other may respond better or worse to an uncertain danger than isolated individuals. We performed experiments involving a novel scenario simulating an unpredictable situation faced by a group in which 2480 subjects in 108 groups had to both communicate information and decide whether to ‘evacuate’. We manipulated the permissible sorts of interpersonal communication and varied group topology and size. Compared to groups of isolated individuals, we find that communication networks suppress necessary evacuations because of the spontaneous and diffuse emergence of false reassurance; yet, communication networks also restrain unnecessary evacuations in situations without disasters. At the individual level, subjects have thresholds for responding to social information that are sensitive to the negativity, but not the actual accuracy, of the signals being transmitted. Social networks can function poorly as pathways for inconvenient truths that people would rather ignore.

scholarly journals Mnemonic convergence in social networks: The emergent properties of cognition at a collective level

2016 ◽  
Vol 113 (29) ◽  
pp. 8171-8176 ◽  
Author(s):  
Alin Coman ◽  
Ida Momennejad ◽  
Rae D. Drach ◽  
Andra Geana
Keyword(s):  
Social Networks ◽  
Network Structure ◽  
Large Scale ◽  
Optimal Strategies ◽  
Emergent Properties ◽  
Social Phenomena ◽  
Collective Memories ◽  
Individual Level ◽  
Social Network Structure ◽  
Social Interactionist

The development of shared memories, beliefs, and norms is a fundamental characteristic of human communities. These emergent outcomes are thought to occur owing to a dynamic system of information sharing and memory updating, which fundamentally depends on communication. Here we report results on the formation of collective memories in laboratory-created communities. We manipulated conversational network structure in a series of real-time, computer-mediated interactions in fourteen 10-member communities. The results show that mnemonic convergence, measured as the degree of overlap among community members’ memories, is influenced by both individual-level information-processing phenomena and by the conversational social network structure created during conversational recall. By studying laboratory-created social networks, we show how large-scale social phenomena (i.e., collective memory) can emerge out of microlevel local dynamics (i.e., mnemonic reinforcement and suppression effects). The social-interactionist approach proposed herein points to optimal strategies for spreading information in social networks and provides a framework for measuring and forging collective memories in communities of individuals.

scholarly journals Mining Unfollow Behavior in Large-Scale Online Social Networks via Spatial-Temporal Interaction

2020 ◽  
Vol 34 (01) ◽  
pp. 254-261
Author(s):  
Haozhe Wu ◽  
Zhiyuan Hu ◽  
Jia Jia ◽  
Yaohua Bu ◽  
Xiangnan He ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Large Scale ◽  
Social Role ◽  
Network Evolution ◽  
Complex Interaction ◽  
Social Network Structure ◽  
Spatial Attributes ◽  
Temporal Interaction

Online Social Networks (OSNs) evolve through two pervasive behaviors: follow and unfollow, which respectively signify relationship creation and relationship dissolution. Researches on social network evolution mainly focus on the follow behavior, while the unfollow behavior has largely been ignored. Mining unfollow behavior is challenging because user's decision on unfollow is not only affected by the simple combination of user's attributes like informativeness and reciprocity, but also affected by the complex interaction among them. Meanwhile, prior datasets seldom contain sufficient records for inferring such complex interaction. To address these issues, we first construct a large-scale real-world Weibo1 dataset, which records detailed post content and relationship dynamics of 1.8 million Chinese users. Next, we define user's attributes as two categories: spatial attributes (e.g., social role of user) and temporal attributes (e.g., post content of user). Leveraging the constructed dataset, we systematically study how the interaction effects between user's spatial and temporal attributes contribute to the unfollow behavior. Afterwards, we propose a novel unified model with heterogeneous information (UMHI) for unfollow prediction. Specifically, our UMHI model: 1) captures user's spatial attributes through social network structure; 2) infers user's temporal attributes through user-posted content and unfollow history; and 3) models the interaction between spatial and temporal attributes by the nonlinear MLP layers. Comprehensive evaluations on the constructed dataset demonstrate that the proposed UMHI model outperforms baseline methods by 16.44 on average in terms of precision. In addition, factor analyses verify that both spatial attributes and temporal attributes are essential for mining unfollow behavior.

The True Believers

2018 ◽  
Author(s):  
Barbara J. Risman
Keyword(s):  
Gender Differences ◽  
Social Networks ◽  
Social Life ◽  
Gender Ideology ◽  
Macro Level ◽  
Individual Level ◽  
Gender Differentiation ◽  
The World ◽  
The Individual ◽  
Gendered Expectations

This is the first data chapter. In this chapter, respondents who are described as true believers in the gender structure, and essentialist gender differences are introduced and their interviews analyzed. They are true believers because, at the macro level, they believe in a gender ideology where women and men should be different and accept rules and requirements that enforce gender differentiation and even sex segregation in social life. In addition, at the interactional level, these Millennials report having been shaped by their parent’s traditional expectations and they similarly feel justified to impose gendered expectations on those in their own social networks. At the individual level, they have internalized masculinity or femininity, and embody it in how they present themselves to the world. They try hard to “do gender” traditionally.

scholarly journals Review of Associations between Built Environment Characteristics and Severe Acute Respiratory Syndrome Coronavirus 2 Infection Risk

2021 ◽  
Vol 18 (14) ◽  
pp. 7561
Author(s):  
Jingjing Wang ◽  
Xueying Wu ◽  
Ruoyu Wang ◽  
Dongsheng He ◽  
Dongying Li ◽  
...  
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Built Environment ◽  
Longitudinal Research ◽  
Empirical Studies ◽  
Infection Risk ◽  
Design Guidelines ◽  
Individual Level ◽  
Transit Accessibility ◽  
Level Data ◽  
Transmission Pathways

The coronavirus disease 2019 pandemic has stimulated intensive research interest in its transmission pathways and infection factors, e.g., socioeconomic and demographic characteristics, climatology, baseline health conditions or pre-existing diseases, and government policies. Meanwhile, some empirical studies suggested that built environment attributes may be associated with the transmission mechanism and infection risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, no review has been conducted to explore the effect of built environment characteristics on the infection risk. This research gap prevents government officials and urban planners from creating effective urban design guidelines to contain SARS-CoV-2 infections and face future pandemic challenges. This review summarizes evidence from 25 empirical studies and provides an overview of the effect of built environment on SARS-CoV-2 infection risk. Virus infection risk was positively associated with the density of commercial facilities, roads, and schools and with public transit accessibility, whereas it was negatively associated with the availability of green spaces. This review recommends several directions for future studies, namely using longitudinal research design and individual-level data, considering multilevel factors and extending to diversified geographic areas.

scholarly journals The Effect of Individual’s Technological Belief and Usage on Their Absorptive Capacity towards Their Learning Behaviour in Learning Environment

2021 ◽  
Vol 13 (2) ◽  
pp. 718
Author(s):  
Thomas Dolmark ◽  
Osama Sohaib ◽  
Ghassan Beydoun ◽  
Kai Wu
Keyword(s):  
Social Networks ◽  
Absorptive Capacity ◽  
Structural Equation Modelling ◽  
Structural Equation ◽  
Social Influences ◽  
Technology Readiness ◽  
Learning Behaviour ◽  
Individual Level ◽  
Equation Modelling ◽  
The Individual

Absorptive capacity is a common barrier to knowledge transfer at the individual level. However, technology absorptive capacity can enhance an individual’s learning behaviour. This study investigates that technology readiness, the tools for knowledge sources, social influences, and social networks influence an individual’s absorptive capacity on an adaptation of the individual learning behaviour. A quantitative approach is used to assess the presence of a causal relationship from the constructs mentioned above. Data were collected from university students in Australia to examine the hypotheses. With 199 responses, a partial least squares structural equation modelling (PLS-SEM) approach was used for the analysis. The results generated mixed findings. Individual’s technological belief in optimism and innovation and social influences had a significantly weaker effect on individual absorptive capacity, which in turn had a significantly weaker impact on their learning behaviour.

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 The Network Structure of Police Misconduct

2019 ◽  
Vol 5 ◽  
pp. 237802311987979 ◽  
Author(s):  
George Wood ◽  
Daria Roithmayr ◽  
Andrew V. Papachristos
Keyword(s):  
Social Networks ◽  
Network Structure ◽  
Police Officers ◽  
Police Misconduct ◽  
Police Departments ◽  
Top Down ◽  
Network Ties ◽  
Individual Level ◽  
Factors Associated ◽  
Using Data

Conventional explanations of police misconduct generally adopt a microlevel focus on deviant officers or a macrolevel focus on the top-down organization of police departments. Between these levels are social networks of misconduct. This study recreates these networks using data on 16,503 complaints and 15,811 police officers over a six-year period in Chicago. We examine individual-level factors associated with receiving a complaint, the basic properties of these misconduct networks, and factors related to officer co-naming in complaints. We find that the incidence of police misconduct is associated with attributes including race, age, and tenure and that almost half of police officers are connected in misconduct ties in broader networks of misconduct. We also find that certain dyadic factors, especially seniority and race, strongly predict network ties and the incidence of group misconduct. Our results provide actionable information regarding possible ways to leverage the co-complaint network structure to reduce misconduct.

scholarly journals Detailed temporal structure of communication networks in groups of songbirds

2016 ◽  
Vol 13 (119) ◽  
pp. 20160296 ◽  
Author(s):  
Dan Stowell ◽  
Lisa Gill ◽  
David Clayton
Keyword(s):  
Communication Networks ◽  
Temporal Structure ◽  
Characteristic Structure ◽  
Call Timing ◽  
Social Network Structure ◽  
Cross Correlation Analysis ◽  
The Social ◽  
Temporal Interactions ◽  
Range Of Influence ◽  
Model Based Analysis

Animals in groups often exchange calls, in patterns whose temporal structure may be influenced by contextual factors such as physical location and the social network structure of the group. We introduce a model-based analysis for temporal patterns of animal call timing, originally developed for networks of firing neurons. This has advantages over cross-correlation analysis in that it can correctly handle common-cause confounds and provides a generative model of call patterns with explicit parameters for the influences between individuals. It also has advantages over standard Markovian analysis in that it incorporates detailed temporal interactions which affect timing as well as sequencing of calls. Further, a fitted model can be used to generate novel synthetic call sequences. We apply the method to calls recorded from groups of domesticated zebra finch ( Taeniopygia guttata ) individuals. We find that the communication network in these groups has stable structure that persists from one day to the next, and that ‘kernels’ reflecting the temporal range of influence have a characteristic structure for a calling individual's effect on itself, its partner and on others in the group. We further find characteristic patterns of influences by call type as well as by individual.

Sign in / Sign up

Export Citation Format

Share Document