Drivers of Social Network Formation: Exploring Brand Homophily

2021 ◽  
Vol 36 (4) ◽  
pp. 91-108
Author(s):  
Inyoung Chae
2006 ◽  
Vol 25 (4) ◽  
pp. 237-246
Author(s):  
Tomas Hellström

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.


Author(s):  
Laurette T. Liesen

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.


2017 ◽  
Vol 103 ◽  
pp. 286-312 ◽  
Author(s):  
Bassel Tarbush ◽  
Alexander Teytelboym

2015 ◽  
Vol 112 (21) ◽  
pp. 6595-6600 ◽  
Author(s):  
Tuan Q. Phan ◽  
Edoardo M. Airoldi

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.


2004 ◽  
Vol 07 (01) ◽  
pp. 77-92 ◽  
Author(s):  
NICOLAS CARAYOL ◽  
PASCALE ROUX

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.


2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Sabina B. Gesell ◽  
Kimberly D. Bess ◽  
Shari L. Barkin

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.


2016 ◽  
Vol 30 (09) ◽  
pp. 1650051 ◽  
Author(s):  
Pei Li ◽  
Jiajun Cheng ◽  
Yingwen Chen ◽  
Hui Wang

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.


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