Peer Group Structure and Adolescent Cigarette Smoking: A Social Network Analysis

1993 ◽  
Vol 34 (3) ◽  
pp. 226 ◽  
Author(s):  
Susan T. Ennett ◽  
Karl E. Bauman
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Cigarette Smoking ◽  
Peer Group ◽  
Group Structure

Influence of Opinion Leaders on Purchase Intention Using Social Network Analysis

2018 ◽  
Vol 10 (1) ◽  
pp. 1-16
Author(s):  
Yi-Fen Chen ◽  
Chia-Wen Tsai ◽  
Yu-Fu Ann
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Purchase Intention ◽  
Mobile Apps ◽  
Peer Group ◽  
Group Structure ◽  
Perceived Value ◽  
Opinion Leader ◽  
Network Centrality

This article examines social network centralities to identify peer group's opinion leader with the aim of determining whether an opinion leader and perceived value influence purchase intention in the field of paid mobile apps. Social network analysis (SNA) and regression analysis are applied to examine the hypotheses within the theoretical framework. The experiment involved a peer group of college students with total of 46 subjects. Using SPSS to analyze the influences of perceived value and the group's opinion leader on purchase intention, the results showed that consumer purchase intention is positively influenced by both the perceived value of paid mobile apps and positive advices given by opinion leader. In addition, an analysis using Ucinet 6 to examine consulting network centrality, friendship network centrality, and information centrality of every member of the group revealed that based on group structure, the group member having the highest centrality has the group's potential to be the opinion leader.

Network Analysis for Economics and Management Studies

2016 ◽  
pp. 1-60 ◽  
Author(s):  
Lucio Biggiero
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Formation ◽  
Competitive Equilibrium ◽  
Group Structure ◽  
Network Modeling ◽  
Descriptive Analysis ◽  
Economic Networks ◽  
Main Research

Sociology and other social sciences have employed network analysis earlier than management and organization sciences, and much earlier than economics, which has been the last one to systematically adopt it. Nevertheless, the development of network economics during last 15 years has been massive, alongside three main research streams: strategic formation network modeling, (mostly descriptive) analysis of real economic networks, and optimization methods of economic networks. The main reason why this enthusiastic and rapidly diffused interest of economists came so late is that the most essential network properties, like externalities, endogenous change processes, and nonlinear propagation processes, definitely prevent the possibility to build a general – and indeed even partial – competitive equilibrium theory. For this paradigm has dominated economics in the last century, this incompatibility operated as a hard brake, and presented network analysis as an inappropriate epistemology. Further, being intrinsically (and often, until recent times, also radically) structuralist, social network analysis was also antithetic to radical methodological individualism, which was – and still is – economics dominant methodology. Though culturally and scientifically influenced by economists in some fields, like finance, banking and industry studies, scholars in management and organization sciences were free from “neoclassical economics chains”, and therefore more ready and open to adopt the methodology and epistemology of social network analysis. The main and early field through which its methods were channeled was the sociology of organizations, and in particular group structure and communication, because this is a research area largely overlapped between sociology and management studies. Currently, network analysis is becoming more and more diffused within management and organization sciences. Mostly descriptive until 15 years ago, all the fields of social network analysis have a great opportunity of enriching and developing its methods of investigation through statistical network modeling, which offers the possibility to develop, respectively, network formation and network dynamics models. They are a good compromise between the much more powerful agent-based simulation models and the usually descriptive (or poorly analytical) methods.

scholarly journals Agonistic Interactions in Pigs–Comparison of Dominance Indices with Parameters Derived from Social Network Analysis in Three Age Groups

Animals ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 929 ◽  
Author(s):  
Kathrin Büttner ◽  
Irena Czycholl ◽  
Katharina Mees ◽  
Joachim Krieter
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Structural Equation ◽  
Dominance Hierarchy ◽  
Rank Order ◽  
Group Structure ◽  
Age Groups ◽  
Agonistic Interactions ◽  
Dominance Indices

Dominance indices are often calculated using the number of won and lost fights of each animal focusing on dyadic interactions. Social network analysis provides new insights into the establishment of stable group structures going beyond the dyadic approach. Thus, it was investigated whether centrality parameters describing the importance of each animal for the network are able to capture the rank order calculated by dominance indices. Therefore, two dominance indices and five centrality parameters based on two network types (initiator-receiver and winner-loser networks) were calculated regarding agonistic interactions observed in three mixing events (weaned piglets, fattening pigs, gilts). Comparing the two network types, the winner-loser networks demonstrated highly positive correlation coefficients between out-degree and outgoing closeness and the dominance indices. These results were confirmed by partial least squares structural equation modelling (PLS-SEM), i.e., about 60% of the variance of the dominance could be explained by the centrality parameters, whereby the winner-loser networks could better illustrate the dominance hierarchy with path coefficients of about 1.1 for all age groups. Thus, centrality parameters can portray the dominance hierarchy providing more detailed insights into group structure which goes beyond the dyadic approach.

scholarly journals Social Network Analysis of a Chimpanzee (Pan troglodytes) Group in Captivity Following the Integration of a New Adult Member

2020 ◽  
Vol 41 (5) ◽  
pp. 683-700
Author(s):  
Sergio Díaz ◽  
Lindsay Murray ◽  
Sam G. B. Roberts ◽  
Paul Rodway
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Pan Troglodytes ◽  
Group Structure ◽  
First Year ◽  
Primate Behavior ◽  
Significant Difference ◽  
In Captivity ◽  
The Stability

AbstractManagement of primates in captivity often presents the challenge of introducing new individuals into a group, and research investigating the stability of the social network in the medium term after the introduction can help inform management decisions. We investigated the behavior of a group of chimpanzees (Pan troglodytes) housed at Chester Zoo, UK over 12 months (divided into three periods of 4 months) following the introduction of a new adult female. We recorded grooming, proximity, other affiliative behaviors, and agonistic behaviors and used social network analysis to investigate the stability, reciprocity, and structure of the group, to examine the effect of rearing history on grooming network position and the role of sex in agonistic behavior. Both the grooming and agonistic networks correlated across all three periods, while affiliative networks correlated only between periods 2 and 3. Males had significantly higher out-degree centrality in agonistic behaviors than females, indicating that they carried out agonistic behaviors more often than females. There was no significant difference in centrality between hand-reared and mother-reared chimpanzees. Overall, the group structure was stable and cohesive during the first year after the introduction of the new female, suggesting that this change did not destabilize the group. Our findings highlight the utility of social network analysis in the study of primate sociality in captivity, and how it can be used to better understand primate behavior following the integration of new individuals.

How small states acquire status: A social network analysis

2018 ◽  
Vol 21 (3) ◽  
pp. 191-213 ◽  
Author(s):  
Phil Baxter ◽  
Jenna Jordan ◽  
Lawrence Rubin
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
International Politics ◽  
Peer Group ◽  
International System ◽  
Small States ◽  
Central Position ◽  
Middle Powers ◽  
International Engagement

A number of recent studies have recognized the importance of status in international politics. While this developing scholarship has largely focused on great and middle powers, the pursuit of status by small states remains underexplored. For example, many studies claim that small states such as Qatar ‘punch above their weight’ in international politics in pursuit of status. How do small states without significant military power acquire status? How can we assess change in status over time? This paper argues that small states can acquire status by increasing their involvement in international politics and one way states can do this is through mediation efforts. Acting as a mediator for international conflict can enhance a small state’s status relative to its peers by demonstrating its relevance and importance in the regional and international system. This public act of mediation produces commonly held beliefs that the mediator state is an influential player in the international system, thus conferring it more status. Social network analysis reveals that as a state increases its international engagement through mediation activities, it can occupy a more central position in important networks, and a higher ranking within its peer group, indicating an increase in status. This increase in status can be translated to greater influence in international politics.

scholarly journals Peer Smoking, Other Peer Attributes, and Adolescent Cigarette Smoking: A Social Network Analysis

2008 ◽  
Vol 9 (2) ◽  
pp. 88-98 ◽  
Author(s):  
Susan T. Ennett ◽  
Robert Faris ◽  
John Hipp ◽  
Vangie A. Foshee ◽  
Karl E. Bauman ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Cigarette Smoking ◽  
Peer Smoking

Network Analysis for Economics and Management Studies

2020 ◽  
pp. 269-328
Author(s):  
Lucio Biggiero
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Formation ◽  
Competitive Equilibrium ◽  
Group Structure ◽  
Network Modeling ◽  
Descriptive Analysis ◽  
Economic Networks ◽  
Main Research

Sociology and other social sciences have employed network analysis earlier than management and organization sciences, and much earlier than economics, which has been the last one to systematically adopt it. Nevertheless, the development of network economics during last 15 years has been massive, alongside three main research streams: strategic formation network modeling, (mostly descriptive) analysis of real economic networks, and optimization methods of economic networks. The main reason why this enthusiastic and rapidly diffused interest of economists came so late is that the most essential network properties, like externalities, endogenous change processes, and nonlinear propagation processes, definitely prevent the possibility to build a general – and indeed even partial – competitive equilibrium theory. For this paradigm has dominated economics in the last century, this incompatibility operated as a hard brake, and presented network analysis as an inappropriate epistemology. Further, being intrinsically (and often, until recent times, also radically) structuralist, social network analysis was also antithetic to radical methodological individualism, which was – and still is – economics dominant methodology. Though culturally and scientifically influenced by economists in some fields, like finance, banking and industry studies, scholars in management and organization sciences were free from “neoclassical economics chains”, and therefore more ready and open to adopt the methodology and epistemology of social network analysis. The main and early field through which its methods were channeled was the sociology of organizations, and in particular group structure and communication, because this is a research area largely overlapped between sociology and management studies. Currently, network analysis is becoming more and more diffused within management and organization sciences. Mostly descriptive until 15 years ago, all the fields of social network analysis have a great opportunity of enriching and developing its methods of investigation through statistical network modeling, which offers the possibility to develop, respectively, network formation and network dynamics models. They are a good compromise between the much more powerful agent-based simulation models and the usually descriptive (or poorly analytical) methods.

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