scholarly journals A natural experiment of social network formation and dynamics

2015 ◽  
Vol 112 (21) ◽  
pp. 6595-6600 ◽  
Author(s):  
Tuan Q. Phan ◽  
Edoardo M. Airoldi
Keyword(s):  
Social Network ◽  
Social Relations ◽  
Natural Experiment ◽  
Social Dynamics ◽  
Network Formation ◽  
High Stress ◽  
Individual Characteristics ◽  
Time Resolved ◽  
Diffusion Of Information ◽  
Social Network Formation

Social networks affect many aspects of life, including the spread of diseases, the diffusion of information, the workers' productivity, and consumers' behavior. Little is known, however, about how these networks form and change. Estimating causal effects and mechanisms that drive social network formation and dynamics is challenging because of the complexity of engineering social relations in a controlled environment, endogeneity between network structure and individual characteristics, and the lack of time-resolved data about individuals' behavior. We leverage data from a sample of 1.5 million college students on Facebook, who wrote more than 630 million messages and 590 million posts over 4 years, to design a long-term natural experiment of friendship formation and social dynamics in the aftermath of a natural disaster. The analysis shows that affected individuals are more likely to strengthen interactions, while maintaining the same number of friends as unaffected individuals. Our findings suggest that the formation of social relationships may serve as a coping mechanism to deal with high-stress situations and build resilience in communities.

Enabling social networks in an R&D organization

2006 ◽  
Vol 25 (4) ◽  
pp. 237-246
Author(s):  
Tomas Hellström
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Qualitative Study ◽  
Network Formation ◽  
Higher Order ◽  
Practical Significance ◽  
Administrative Unit ◽  
High Level ◽  
Social Network Formation

This paper presents a qualitative study of mechanisms enabling social network formation in the R&D unit of a large technology-based organization. Drawing on interviews with 37 high-level technical and administrative unit members, a number of social network enablers could be discerned, which related to the need for effective location mechanisms, special “enrolment spaces”, and mechanisms for forging contacts. It was also possible to identify a number of higher-order factors for facilitation of network formation, namely hierarchical enablers and communicative and assimilative factors. Based on these results, the paper makes suggestions as to the theoretical and practical significance of social network enabling mechanisms in R&D organizations.

Feminist and Evolutionary Perspectives of Female-Female Competition, Status Seeking, and Social Network Formation

2015 ◽  
Author(s):  
Laurette T. Liesen
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Reproductive Success ◽  
Reproductive Strategies ◽  
Network Formation ◽  
Female Competition ◽  
Status Seeking ◽  
Social Network Formation ◽  
Evolutionary Perspectives

During the 1980s and 1990s, feminist evolutionists were instrumental in demonstrating that primate females, including girls and women, can be aggressive and seek status within their groups. Building on their insights, researchers from across disciplines have found that females use a variety of direct and indirect tactics as they pursue their reproductive success. To better understand women’s aggression and status seeking, one also must examine their social networks. Women must not only deal with the dynamics within their groups, they also must deal with pressures from other groups. Success in maintaining connections in one’s social network is vital for access to the various resources women need for their own reproductive success and to keep competitors in check. Overall, women’s social networks, while serving both supportive and competitive functions, profoundly impact on the reproductive future of women and especially the survival and future reproductive strategies of their children.

scholarly journals Social groups and social network formation

2017 ◽  
Vol 103 ◽  
pp. 286-312 ◽  
Author(s):  
Bassel Tarbush ◽  
Alexander Teytelboym
Keyword(s):  
Social Network ◽  
Network Formation ◽  
Social Groups ◽  
Social Network Formation

How Social Network and Opinion Leaders Affect the Adoption of New Products

2011 ◽  
Vol 3 (1) ◽  
pp. 16-25 ◽  
Author(s):  
Raghuram Iyengar ◽  
Christophe Van den Bulte ◽  
John Eichert ◽  
Bruce West
Keyword(s):  
Social Network ◽  
Peer Influence ◽  
Social Dynamics ◽  
Word Of Mouth ◽  
Individual Characteristics ◽  
Opinion Leaders ◽  
Central Position ◽  
Self Confidence ◽  
Marketing Effectiveness ◽  
The Social

Abstract Do word-of-mouth and other peer influence processes really affect how quickly people adopt a new product? Can one identify the most influential customers and hence those who are good seeding points for a word-of-mouth marketing campaign? Can one also identify those customers most likely to be influenced by their peers? A pharmaceutical company seeking to improve its marketing effectiveness by leveraging social dynamics among physicians set out to answer these questions. There is indeed evidence of social influence, even after controlling for sales calls and individual characteristics. Also, people who are central in the network and those who use the product intensively are more influential. Finally, people who view themselves as opinion leaders are less affected by peer influence, whereas people who others really turn to for information or advice are not differentially affected. This last finding suggests that self-reported opinion leadership captures self-confidence, whereas a central position in the social network captures true leadership. Since sociometric techniques identify true opinion leaders more effectively than self-reports do, word-of-mouth programs targeting sociometric leaders are expected to be more effective than programs targeting self-reported leaders

BEHAVIORAL FOUNDATIONS AND EQUILIBRIUM NOTIONS FOR SOCIAL NETWORK FORMATION PROCESSES

2004 ◽  
Vol 07 (01) ◽  
pp. 77-92 ◽  
Author(s):  
NICOLAS CARAYOL ◽  
PASCALE ROUX
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Formation Process ◽  
Network Formation ◽  
Small World ◽  
Payoff Function ◽  
Formation Processes ◽  
Limiting Distributions ◽  
Stochastically Stable ◽  
Social Network Formation

This paper develops a framework for studying social network formation. Partly built upon a formalism used in theoretical economics, the network formation process we introduce is locally driven by agents who maximize a given individual payoff function. We examine two simple models and observe the limiting distributions of stochastically stable networks. We find that these networks share some of the features observed for social networks. In particular, we find critical values of the parameters for which the selected networks exhibit small world properties.

scholarly journals Understanding the Social Networks That Form within the Context of an Obesity Prevention Intervention

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Sabina B. Gesell ◽  
Kimberly D. Bess ◽  
Shari L. Barkin
Keyword(s):  
Social Networks ◽  
Social Network ◽  
School Readiness ◽  
Obesity Prevention ◽  
Network Formation ◽  
Group Level ◽  
The Social ◽  
Similar Body ◽  
Child Bmi ◽  
Social Network Formation

Background. Antiobesity interventions have generally failed. Research now suggests that interventions must be informed by an understanding of the social environment.Objective. To examine if new social networks form between families participating in a group-level pediatric obesity prevention trial.Methods. Latino parent-preschool child dyads (N=79) completed the 3-month trial. The intervention met weekly in consistent groups to practice healthy lifestyles. The control met monthly in inconsistent groups to learn about school readiness. UCINET and SIENA were used to examine network dynamics.Results. Children’s mean age was 4.2 years (SD=0.9), and 44% were overweight/obese (BMI≥85th percentile). Parents were predominantly mothers (97%), with a mean age of 31.4 years (SD=5.4), and 81% were overweight/obese (BMI≥25). Over the study, a new social network evolved among participating families. Parents selectively formed friendship ties based on child BMI z-score, (t=2.08;P<.05). This reveals the tendency for mothers to form new friendships with mothers whose children have similar body types.Discussion. Participating in a group-level intervention resulted in new social network formation. New ties were greatest with mothers who had children of similar body types. This finding might contribute to the known inability of parents to recognize child overweight.

A model of social network formation under the impact of structural balance

2016 ◽  
Vol 30 (09) ◽  
pp. 1650051 ◽  
Author(s):  
Pei Li ◽  
Jiajun Cheng ◽  
Yingwen Chen ◽  
Hui Wang
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Formation ◽  
Common Phenomenon ◽  
Structural Balance ◽  
Negative Links ◽  
Social Network Formation ◽  
The Impact ◽  
Negative Relationships ◽  
Industrial Societies

Social networks have attracted remarkable attention from both academic and industrial societies and it is of great importance to understand the formation of social networks. However, most existing research cannot be applied directly to investigate social networks, where relationships are heterogeneous and structural balance is a common phenomenon. In this paper, we take both positive and negative relationships into consideration and propose a model to characterize the process of social network formation under the impact of structural balance. In this model, a new node first establishes a link with an existing node and then tries to connect to each of the newly connected node’s neighbors. If a new link is established, the type of this link is determined by structural balance. Then we analyze the degree distribution of the generated network theoretically, and estimate the fractions of positive and negative links. All analysis results are verified by simulations. These results are of importance to understand the formation of social networks, and the model can be easily extended to consider more realistic situations.

Sign in / Sign up

Export Citation Format

Share Document