Multilayer Social Networks

Dickison, Mark E.; Magnani, Matteo; Rossi, Luca

doi:10.1017/cbo9781139941907

Cited by 154 publications

(120 citation statements)

References 187 publications

Supporting

Mentioning

100

Contrasting

Unclassified

Order By: Relevance

“…This basic approach involves completely separating the attribute visualization from the graph structure. To better relate the relationship between networks structure and attributes, the attributes may be integrated into the network visualization itself (referred to as augmented network visualization by [DMR16a, RM15]) or a linked view brushing approach maybe taken, by which the relevant related nodes would be highlighted in a network view, when selected in the attribute visualization and vice versa (Task category B ).…”

Section: Survey Of Multilayer Graph Visualizationsmentioning

confidence: 99%

“…Examples of multilayer networks can be found in the domains of biology (the so‐called ‘omics’ layers), epidemiology [WX12, SMSB12, PSCVMV15], sociology (in a broad sense, including fields such as criminology, for instance) [BS85, LP99, GB07, FPSG10, GKL*13, CMF*14, BGRM15, DMR16a], digital humanities [MDG16, DHRL*12, SGo16], civil infrastructure [CGGZ*13, Duc17, Der17] and more. Multilayer networks have been explicitly recognized as promising for biological analysis [GMD*18].…”

Section: Introductionmentioning

confidence: 99%

“…Other definitions of layers are also possible as illustrated in Section 2. FPSG10, GKL*13, CMF*14, BGRM15,DMR16a], digital humanities [MDG16,DHRL*12,SGo16], civil infrastructure [CGGZ*13, Duc17, Der17] and more. Multilayer networks have been explicitly recognized as promising for biological analysis [GMD*18].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The State of the Art in Multilayer Network Visualization

McGee

Ghoniem

Mélançon

et al. 2019

Computer Graphics Forum

View full text Add to dashboard Cite

Modelling relationship between entities in real‐world systems with a simple graph is a standard approach. However, reality is better embraced as several interdependent subsystems (or layers). Recently, the concept of a multilayer network model has emerged from the field of complex systems. This model can be applied to a wide range of real‐world data sets. Examples of multilayer networks can be found in the domains of life sciences, sociology, digital humanities and more. Within the domain of graph visualization, there are many systems which visualize data sets having many characteristics of multilayer graphs. This report provides a state of the art and a structured analysis of contemporary multilayer network visualization, not only for researchers in visualization, but also for those who aim to visualize multilayer networks in the domain of complex systems, as well as those developing systems across application domains. We have explored the visualization literature to survey visualization techniques suitable for multilayer graph visualization, as well as tools, tasks and analytic techniques from within application domains. This report also identifies the outstanding challenges for multilayer graph visualization and suggests future research directions for addressing them.

show abstract

Section: Survey Of Multilayer Graph Visualizationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The State of the Art in Multilayer Network Visualization

McGee

Ghoniem

Mélançon

et al. 2019

Computer Graphics Forum

View full text Add to dashboard Cite

show abstract

“…In the early 90s, six themes (turnover/absenteeism, power, work attitudes, job design, leadership, and motivation) dominated the research of microorganisational behaviour [54]. Recently, multilayer networks are becoming widely used in the analysis of social networks where people interact with each other in multiple ways like via mobile phone and emails [55][56][57][58][59]. In this paper, we make the first attempt to integrate such analysis to the modelling and optimisation of production process.…”

Section: Analysis Of the Flexibility Of Operator Assignmentmentioning

confidence: 99%

Multilayer Network‐Based Production Flow Analysis

2018

View full text Add to dashboard Cite

A multilayer network model for the exploratory analysis of production technologies is proposed. To represent the relationship between products, parts, machines, resources, operators, and skills, standardized production and product-relevant data are transformed into a set of bi-and multipartite networks. This representation is beneficial in production flow analysis (PFA) that is used to identify improvement opportunities by grouping similar groups of products, components, and machines. It is demonstrated that the goal-oriented mapping and modularity-based clustering of multilayer networks can serve as a readily applicable and interpretable decision support tool for PFA, and the analysis of the degrees and correlations of a node can identify critically important skills and resources. The applicability of the proposed methodology is demonstrated by a well-documented benchmark problem of a wire-harness production process. The results confirm that the proposed multilayer network can support the standardized integration of production-relevant data and exploratory analysis of strongly interconnected production systems.

show abstract

“…It should be emphasized that neglecting such a kind of complex organization by reducing the whole system to a single network (e.g., through some kind of projection, or by aggregation), has been shown to be much less informative than the multilayer representation [14]. For the above mentioned reasons, multilayer networks are experiencing an increasing interest from the scientific community, leading to an explosion of scientific papers in many areas of science, thus becoming one of the most used tools for interdisciplinary research [15], [16], [11], [13], [17], [18], [12], [19], [20,21], [22], [23].…”

Section: Introductionmentioning

confidence: 99%

Modularity in Multilayer Networks Using Redundancy-Based Resolution and Projection-Based Inter-Layer Coupling

Amelio

Mangioni

Tagarelli

2020

IEEE Trans. Netw. Sci. Eng.

View full text Add to dashboard Cite

The generalized version of modularity for multilayer networks, a.k.a. multislice modularity, is characterized by two model parameters, namely resolution factor and inter-layer coupling factor. The former corresponds to a notion of layer-specific relevance, whereas the inter-layer coupling factor represents the strength of node connections across the network layers. Despite the potential of this approach, the setting of both parameters can be arbitrarily selected, without considering specific characteristics from the topology of the multilayer network as well as from an available community structure. Also, the multislice modularity is not designed to explicitly model order relations over the layers, which is of prior importance for dynamic networks.This paper aims to overcome the main limitations of the multislice modularity by introducing a new formulation of modularity for multilayer networks. We revise the role and semantics of both the resolution and inter-layer coupling factors based on information available from the within-layer and inter-layer structures of the multilayer communities. Also, our proposed multilayer modularity is general enough to consider orderings of network layers and their constraints on layer coupling. Experiments were carried out on synthetic and real-world multilayer networks using state-of-the-art approaches for multilayer community detection. The obtained results have shown the meaningfulness of the proposed modularity, revealing the effects of different combinations of the resolution and inter-layer coupling functions. This work also represents a starting point for the development of new optimization methods for community detection in multilayer networks.

show abstract

Multilayer Social Networks

Cited by 154 publications

References 187 publications

The State of the Art in Multilayer Network Visualization

The State of the Art in Multilayer Network Visualization

Multilayer Network‐Based Production Flow Analysis

Modularity in Multilayer Networks Using Redundancy-Based Resolution and Projection-Based Inter-Layer Coupling

Contact Info

Product

Resources

About