scholarly journals Reconstructing irreducible links in temporal networks: which tool to choose depends on the network size

2020 ◽  
Vol 1 (1) ◽  
pp. 015001 ◽  
Author(s):  
Matthieu Nadini ◽  
Alessandro Rizzo ◽  
Maurizio Porfiri
Keyword(s):  
Network Size ◽  
Temporal Networks

Limit of a nonpreferential attachment multitype network model

2017 ◽  
Vol 31 (05) ◽  
pp. 1750026 ◽  
Author(s):  
Yilun Shang
Keyword(s):  
Complex Networks ◽  
Network Model ◽  
Theoretical Framework ◽  
Network Size ◽  
Temporal Networks ◽  
Limit Theory ◽  
Time Order ◽  
Graph Limit

Here, we deal with a model of multitype network with nonpreferential attachment growth. The connection between two nodes depends asymmetrically on their types, reflecting the implication of time order in temporal networks. Based upon graph limit theory, we analytically determined the limit of the network model characterized by a kernel, in the sense that the number of copies of any fixed subgraph converges when network size tends to infinity. The results are confirmed by extensive simulations. Our work thus provides a theoretical framework for quantitatively understanding grown temporal complex networks as a whole.

Extraverts Have Larger Social Network Layers

2011 ◽  
Vol 32 (3) ◽  
pp. 161-169 ◽  
Author(s):  
Thomas V. Pollet ◽  
Sam G. B. Roberts ◽  
Robin I. M. Dunbar
Keyword(s):  
Social Network ◽  
Social Relationships ◽  
Outer Layer ◽  
Network Size ◽  
Emotional Intensity ◽  
Emotional Closeness ◽  
Network Layer ◽  
Network Layers ◽  
Social Network Size

Previous studies showed that extraversion influences social network size. However, it is unclear how extraversion affects the size of different layers of the network, and how extraversion relates to the emotional intensity of social relationships. We examined the relationships between extraversion, network size, and emotional closeness for 117 individuals. The results demonstrated that extraverts had larger networks at every layer (support clique, sympathy group, outer layer). The results were robust and were not attributable to potential confounds such as sex, though they were modest in size (raw correlations between extraversion and size of network layer, .20 < r < .23). However, extraverts were not emotionally closer to individuals in their network, even after controlling for network size. These results highlight the importance of considering not just social network size in relation to personality, but also the quality of relationships with network members.

HEXACO personality factors and their associations with Facebook use and Facebook network characteristics

2018 ◽  
Author(s):  
Riana Brown ◽  
Sam G. B. Roberts ◽  
Thomas V. Pollet
Keyword(s):  
Social Networks ◽  
Network Size ◽  
Openness To Experience ◽  
Personality Factors ◽  
Number Of Clusters ◽  
Network Characteristics ◽  
Online Networks ◽  
Facebook Use ◽  
Objectively Measured ◽  
Size And Structure

Personality factors affect the properties of ‘offline’ social networks, but how they are associated with the structural properties of online networks is still unclear. We investigated how the six HEXACO personality factors (Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness and Openness to Experience) relate to Facebook use and three objectively measured Facebook network characteristics - network size, density, and number of clusters. Participants (n = 107, mean age = 20.6, 66% female) extracted their Facebook networks using the GetNet app, completed the 60-item HEXACO questionnaire and the Facebook Usage Questionnaire. Users high in Openness to Experience spent less time on Facebook. Extraversion was positively associated with network size and the number of network clusters (but not after controlling for size). These findings suggest that personality factors are associated with Facebook use and the size and structure of Facebook networks, and that personality is an important influence on both online and offline sociality.

Smartphone sensing of social interactions in people with and without schizophrenia

2020 ◽  
Author(s):  
Daniel Fulford ◽  
Jasmine Mote ◽  
Rachel Gonzalez ◽  
Samuel Abplanalp ◽  
Yuting Zhang ◽  
...  
Keyword(s):  
Social Behavior ◽  
Social Functioning ◽  
Social Activity ◽  
Network Size ◽  
Social Impairment ◽  
Schizophrenia Spectrum Disorders ◽  
Social Network Size ◽  
Digital Phenotyping ◽  
Ecological Momentary

Social impairment is a cardinal feature of schizophrenia spectrum disorders (SZ). Smaller social network size, diminished social skills, and loneliness are highly prevalent. Existing, gold-standard assessments of social impairment in SZ often rely on self-reported information that depends on retrospective recall and detailed accounts of complex social behaviors. This is particularly problematic in people with SZ given characteristic cognitive impairments and reduced insight. Ecological Momentary Assessment (EMA; repeated self-reports completed in the context of daily life) allows for the measurement of social behavior as it occurs in vivo, yet still relies on participant input. Momentary characterization of behavior using smartphone sensors (e.g., GPS, microphone) may also provide ecologically valid indicators of social functioning. In the current study we tested associations between both active (e.g., EMA-reported number of interactions) and passive (GPS-based mobility, conversations captured by microphone) smartphone-based measures of social activity and measures of social functioning and loneliness to examine the promise of such measures for understanding social impairment in SZ. Our results indicate that passive markers of mobility were more consistently associated with EMA measures of social behavior in controls than in people with SZ. Furthermore, dispositional loneliness showed associations with mobility metrics in both groups, while general social functioning was less related to these metrics. Finally, interactions detected in the ambient audio were more tied to social functioning in SZ than in controls. Findings speak to the promise of smartphone-based digital phenotyping as an approach to understanding objective markers of social activity in people with and without schizophrenia.

Probabilistic Temporal Networks.

1996 ◽  
Author(s):  
Eugene Santos ◽  
Young Jr. ◽  
Joel D.
Keyword(s):  
Temporal Networks

Network Size and Connectivity in Mobile and Stationary Ad Hoc Networks

2014 ◽  
Author(s):  
Lance Joneckis ◽  
Corinne Kramer ◽  
David Sparrow ◽  
David Tate
Keyword(s):  
Ad Hoc Networks ◽  
Ad Hoc ◽  
Network Size ◽  
Hoc Networks

Models of network formation

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Degree Distribution ◽  
Network Formation ◽  
Preferential Attachment ◽  
Network Size ◽  
Large Network ◽  
Citation Networks ◽  
Airline Networks ◽  
Attachment Model ◽  
Delivery Networks

This chapter describes models of the growth or formation of networks, with a particular focus on preferential attachment models. It starts with a discussion of the classic preferential attachment model for citation networks introduced by Price, including a complete derivation of the degree distribution in the limit of large network size. Subsequent sections introduce the Barabasi-Albert model and various generalized preferential attachment models, including models with addition or removal of extra nodes or edges and models with nonlinear preferential attachment. Also discussed are node copying models and models in which networks are formed by optimization processes, such as delivery networks or airline networks.

scholarly journals Higher-order temporal network effects through triplet evolution

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qing Yao ◽  
Bingsheng Chen ◽  
Tim S. Evans ◽  
Kim Christensen
Keyword(s):  
Real World ◽  
Link Prediction ◽  
Higher Order ◽  
Prediction Algorithm ◽  
Interaction Patterns ◽  
Temporal Networks ◽  
World Systems ◽  
Order Interaction ◽  
Space And Time ◽  
Pairwise Interactions

AbstractWe study the evolution of networks through ‘triplets’—three-node graphlets. We develop a method to compute a transition matrix to describe the evolution of triplets in temporal networks. To identify the importance of higher-order interactions in the evolution of networks, we compare both artificial and real-world data to a model based on pairwise interactions only. The significant differences between the computed matrix and the calculated matrix from the fitted parameters demonstrate that non-pairwise interactions exist for various real-world systems in space and time, such as our data sets. Furthermore, this also reveals that different patterns of higher-order interaction are involved in different real-world situations. To test our approach, we then use these transition matrices as the basis of a link prediction algorithm. We investigate our algorithm’s performance on four temporal networks, comparing our approach against ten other link prediction methods. Our results show that higher-order interactions in both space and time play a crucial role in the evolution of networks as we find our method, along with two other methods based on non-local interactions, give the best overall performance. The results also confirm the concept that the higher-order interaction patterns, i.e., triplet dynamics, can help us understand and predict the evolution of different real-world systems.

scholarly journals Temporal gravity model for important node identification in temporal networks

2021 ◽  
Vol 147 ◽  
pp. 110934
Author(s):  
Jialin Bi ◽  
Ji Jin ◽  
Cunquan Qu ◽  
Xiuxiu Zhan ◽  
Guanghui Wang ◽  
...  
Keyword(s):  
Gravity Model ◽  
Temporal Networks ◽  
Temporal Gravity

scholarly journals Dynamic Capability and Open-Source Strategy in the Age of Digital Transformation

2021 ◽  
Vol 7 (3) ◽  
pp. 175
Author(s):  
Nobuyuki Fukawa ◽  
Yanzhi Zhang ◽  
Sunil Erevelles
Keyword(s):  
Operating System ◽  
Open Source ◽  
Customer Value ◽  
Big Data Analytics ◽  
Idea Generation ◽  
Network Size ◽  
Digital Transformation ◽  
Mobile Technologies ◽  
Dynamic Capability ◽  
Digital Platforms

Today, Industry 4.0 technologies, such as Big Data analytics and mobile technologies, are forcing firms to seek new ways to create and deliver customer value. We argue that the Android project, one of the most successful open-source digital platforms, reflects a new business model in the age of digital transformation. In the Android community, application developers create and sell applications for the Android operating system provided by the open-source firm (Google), and share the profit with Google. Such an open-source strategy forces the open-source firm to give up the profits from selling the operating system to customers. A firm generally chooses an open-source strategy to increase its user network size. Using the concept of creative intensity, or the speed of idea generation, we offer a new explanation regarding the benefits of an open-source strategy in the age of digital transformation. We investigate how to enhance creative intensity and profit on the open-source digital platform. Our model suggests that an open-source strategy effectively manages the diminishing value of ideas and, thus, facilitates the dynamic capability of an open-source firm.

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