Visualization techniques for categorical analysis of social networks with multiple edge sets

Crnovrsanin, Tarik; Muelder, Chris; Faris, Robert; Felmlee, Diane; Liu, Kwan

doi:10.1016/j.socnet.2013.12.002

Cited by 47 publications

(41 citation statements)

References 14 publications

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“…Data sets within Social Network analysis frequently contain multiple types of edges (to support examining the different types of relationships between people, e.g. more recently [CMF*14], but also in much earlier work such as [BS85, LP99]), or multiple types (or modes) of nodes, e.g. modelling a citation network containing researchers, institutions and publications [GKL*13].…”

Section: Multilayer Network and Related Conceptsmentioning

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%

“…In the area of network visualization, many systems visualize data sets having many characteristics of multilayer networks, albeit under a different title. Multi‐label, multi‐edge, multirelational, multiplex [RMM15, CGGZ*13], heterogeneous [DHRL*12, SKB*14], multimodal [GKL*13, HS09], multiple edge set networks [CMF*14], interdependent networks [GBSH12], interconnected networks [SMSB12] and networks of networks [KPB15] are among the many names given to various types of data that are encapsulated by the multilayer networks definition of Kivelä et al . [KAB*14].…”

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

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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.

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Section: Multilayer Network and Related Conceptsmentioning

confidence: 99%

Section: Introductionmentioning

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

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“…Using this technique, [12] conducted a study on aggression in schools. Their research led to the development of a graphic model, which combines the sociogram and statistics to determine if certain populations seem more affected than others by the problems of aggression.…”

Section: Literature Reviewmentioning

confidence: 99%

Measuring Human Risks in Service: A New Model

Barbieri¹,

Fragnière²,

Grandbois³

et al. 2017

JSSM

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The modeling of a customer experience realized through a service blueprint is useful for visualizing the structures and processes involved in its production. However, the classical service blueprint fails to consider the contribution of human factors-motivation, emotion, satisfaction, etc.-that are essential elements of service interactions and can represent important risks of non-quality. Consequently, we have developed an enhanced service blueprint dedicated to Enterprise Risk Management (ERM), which includes the human factor dimension. In order to take into account the human factor dimension in the service blueprinting syntax, we include a sociogram. A sociogram is a graph whose nodes are linked together by arrows expressing sociological and psychological variables. Thus we are able to measure and visually identify the areas at risk in an integrated manner, those which are typically attached to the dominant human factor component of service productions. To illustrate this new ERM modeling concept, we have developed a case study related to a service at the reception of a luxury hotel. We are thus able to show the advantages of using the service blueprinting approach compared to the classical risk mapping process in the context of ERM.

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“…Recent work on constructing visually interpretable social networks has focused on careful data reduction, either by suppressing nodes entirely in favor of contour-style diagrams (Moody & Light 2006; Moody 2004), deleting or “bundling” edges to highlight structure (Crnovrsanin et al 2012). Other work has focused explicitly on quantifying the layout model using stress or MDS-related techniques (Brandes et al 2012; Frank & Yasumoto 1998; Brandes & Pich 2006).…”

Section: Visualization In Practicementioning

confidence: 99%

Data Visualization in Sociology

2014

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Visualizing data is central to social scientific work. Despite a promising early beginning, sociology has lagged in the use of visual tools. We review the history and current state of visualization in sociology. Using examples throughout, we discuss recent developments in ways of seeing raw data and presenting the results of statistical modeling. We make a general distinction between those methods and tools designed to help explore datasets, and those designed to help present results to others. We argue that recent advances should be seen as part of a broader shift towards easier sharing of the code and data both between researchers and with wider publics, and encourage practitioners and publishers to work toward a higher and more consistent standard for the graphical display of sociological insights.

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Visualization techniques for categorical analysis of social networks with multiple edge sets

Cited by 47 publications

References 14 publications

The State of the Art in Multilayer Network Visualization

The State of the Art in Multilayer Network Visualization

Measuring Human Risks in Service: A New Model

Data Visualization in Sociology

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