A friendship network based on random and triadic-closure in a fixed community

2015 ◽  
pp. 29-34
Author(s):  
D Zhao ◽  
K Zhao ◽  
J Yang ◽  
J Sha
Keyword(s):  
Friendship Network ◽  
Triadic Closure

College Friendship Network Diversity, Current Closeness, and Graduates' Political Attitudes

2007 ◽  
Author(s):  
Nichole Thompson ◽  
Tim Abraham ◽  
Ray Parr ◽  
Ryan Halley ◽  
Kate Lachowsky ◽  
...  
Keyword(s):  
Political Attitudes ◽  
Friendship Network ◽  
Network Diversity

scholarly journals Friendship paradox in growth networks: analytical and empirical analysis

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Sergei P. Sidorov ◽  
Sergei V. Mironov ◽  
Alexey A. Grigoriev
Keyword(s):  
Real World ◽  
Preferential Attachment ◽  
Empirical Studies ◽  
Mean Field ◽  
Network Models ◽  
Average Degree ◽  
Closure Model ◽  
Triadic Closure ◽  
Attachment Mechanism ◽  
Over Time

AbstractMany empirical studies have shown that in social, citation, collaboration, and other types of networks in real world, the degree of almost every node is less than the average degree of its neighbors. This imbalance is well known in sociology as the friendship paradox and states that your friends are more popular than you on average. If we introduce a value equal to the ratio of the average degree of the neighbors for a certain node to the degree of this node (which is called the ‘friendship index’, FI), then the FI value of more than 1 for most nodes indicates the presence of the friendship paradox in the network. In this paper, we study the behavior of the FI over time for networks generated by growth network models. We will focus our analysis on two models based on the use of the preferential attachment mechanism: the Barabási–Albert model and the triadic closure model. Using the mean-field approach, we obtain differential equations describing the dynamics of changes in the FI over time, and accordingly, after obtaining their solutions, we find the expected values of this index over iterations. The results show that the values of FI are decreasing over time for all nodes in both models. However, for networks constructed in accordance with the triadic closure model, this decrease occurs at a much slower rate than for the Barabási–Albert graphs. In addition, we analyze several real-world networks and show that their FI distributions follow a power law. We show that both the Barabási–Albert and the triadic closure networks exhibit the same behavior. However, for networks based on the triadic closure model, the distributions of FI are more heavy-tailed and, in this sense, are closer to the distributions for real networks.

scholarly journals Gossip, sabotage, and friendship network dataset

Data in Brief ◽  
2021 ◽  
pp. 107717
Author(s):  
Meltem Yucel ◽  
Gustav R. Sjobeck ◽  
Rebecca Glass ◽  
Joshua Rottman
Keyword(s):  
Friendship Network

scholarly journals Overchoosing: A Mechanism of Tie-Formation in Social Networks

2020 ◽  
Author(s):  
Tasuku Igarashi ◽  
Johank Koskinen
Keyword(s):  
Social Networks ◽  
Formation Process ◽  
Goodness Of Fit ◽  
Network Data ◽  
Formation Processes ◽  
Friendship Network ◽  
Fundamental Mechanism

We introduce the concept of overchoosing as a fundamental mechanism of tie formation in directed social networks. The parameter represents a tendency for actors to send a lot of ties but receive few nominations back, something which implies the importance of modeling reciprocity violation as a basic tie-formation process. Analyzing large friendship network data (N = 1,575) by the stochastic actor-oriented models revealed that, under controlling for several endogenous tie formation processes, the parameter captured the formation of open triads and substantially improved the goodness of fit of the model to the data.

Friendship Network Satisfaction: A multifaceted construct scored as a unidimensional scale

2021 ◽  
pp. 026540752110256
Author(s):  
Victor A. Kaufman ◽  
Jacqueline C. Perez ◽  
Steven P. Reise ◽  
Thomas N. Bradbury ◽  
Benjamin R. Karney
Keyword(s):  
Item Response ◽  
Well Being ◽  
General Factor ◽  
Item Pool ◽  
Friendship Network ◽  
Factor Analyses ◽  
Advance Research ◽  
Factor Modeling ◽  
Correlated Factors ◽  
Unidimensional Scale

Although satisfying friendships are crucial for well-being throughout adulthood, measures of friendship satisfaction have been limited by: (1) item content relevant to children only, (2) a focus on single relationships rather than the friendship network, and (3) disagreement about the number of dimensions necessary to capture the construct. To overcome these limitations, we assembled an item pool from a number of existing measures, created additional items drawn from research on friendships, and then examined the structure and psychometric properties of those items in two online surveys of over 2000 respondents each. Factor analyses consistently identified two correlated factors—closeness and socializing—but bi-factor modeling revealed that scores on both subscales load strongly on a general factor, suggesting that the multifaceted content can be scored efficiently as a unidimensional composite. Analyses using item response theory (IRT) supported the creation of a reliable 14-item instrument that demonstrated adequate convergent and predictive validity. Thus, the Friendship Network Satisfaction (FNS) Scale is a psychometrically sound tool to advance research on friendships across the lifespan.

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