Analysis and Visualization of Dynamic Networks

Zaidi, Faraz; Muelder, Chris; Sallaberry, Arnaud

doi:10.1007/978-1-4614-6170-8_382

Cited by 7 publications

(2 citation statements)

References 24 publications

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“…The overlap of nodes in these conditions is not appropriated when trying to extract information from the network. Zaidi et al [94] and Aggarwal and Subbian [27] presented an overview of the different techniques and methods that exist for the analysis and visualization of dynamic networks. It included the discussion of the basic definitions, formal notations and a set of the most important and recent work regarding analysis and the visualization of dynamic networks.…”

Section: Challenges Of Evolving Network' Visualizationmentioning

confidence: 99%

Social Media and Journalism

Gulyás¹

2016

The Routledge Companion to Digital Journalism Studies

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Recent research has demonstrated how comment threads published beneath online news articles are being transformed into fluid interfaces between professional journalists, their work and their audiences. Today's audience-members are not only able to respond to published narratives but to embellish and, potentially, contest them: by posting comments based on personal knowledge about an issue and even using eyewitness testimony to directly affirm or challenge a story's details. Though often stylistically "messy," such comment posts go beyond merely manifesting and magnifying news discourses-let alone simply reacting to them. Rather, as on social media, posters can publicly discuss and debate the meaning and significance of stories, with the more informed and assertive among them contributing content so significant that it reshapes the texts themselves. In so doing, such claims-makers and counter claims-makers become hybrids of journalists (news producers), audiencemembers (news consumers) and claims-makers (news sources). Drawing on the author's recent empirical findings, this chapter argues that online news has entered a dynamic but disruptive new phase in which journalistic authority may increasingly be contested, as "audience-members" begin to compete with "reporters" for authorship of news narratives.

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Section: Challenges Of Evolving Network' Visualizationmentioning

confidence: 99%

Social Media and Journalism

Gulyás¹

2016

The Routledge Companion to Digital Journalism Studies

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“…[AAK*14] have given an overview of temporal multivariate graphs concentrating on node‐link diagrams and surveying applications in software engineering in closer detail. Also, Zaidi [ZMS14] summarize parts of the state of the art concerning node‐link diagrams. Kerracher et al .…”

Section: Introductionmentioning

confidence: 99%

A Taxonomy and Survey of Dynamic Graph Visualization

Beck

Burch

Diehl

et al. 2016

Computer Graphics Forum

283

249

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Dynamic graph visualization focuses on the challenge of representing the evolution of relationships between entities in readable, scalable and effective diagrams. This work surveys the growing number of approaches in this discipline. We derive a hierarchical taxonomy of techniques by systematically categorizing and tagging publications. While static graph visualizations are often divided into node-link and matrix representations, we identify the representation of time as the major distinguishing feature for dynamic graph visualizations: either graphs are represented as animated diagrams or as static charts based on a timeline. Evaluations of animated approaches focus on dynamic stability for preserving the viewer's mental map or, in general, compare animated diagrams to timeline-based ones. A bibliographic analysis provides insights into the organization and developmentof the field and its community. Finally, we identify and discuss challenges for future research. We also provide feedback from experts, collected with a questionnaire, which gives a broad perspective of these challenges and the current state of the field.

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Identifying key actors in an international crisis using dynamic network analysis

Tawadros

Soliman

2019

JHASS

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Purpose The purpose of this study is to examine the extent to which dynamic network analysis (DNA), text mining and natural language processing (NLP) are helpful research tools in identifying the key actors in a complex international crisis. The study uses these tools to identify the key actors in the Syrian crisis as a case study to validate the proposed algorithm. Design/methodology/approach To achieve its main purpose, the study uses a collection of three methodologies, namely, DNA, text mining and NLP. Findings The results of the analysis show four key actors in the Syrian crisis, namely, Russia, the USA, Turkey and China. The results also reveal changes in their powerful positions from 2012 to 2016, which matches the changes that occurred in the real world. The matching between the findings of the proposed algorithm and the real world events that happened in Syria validate our proposed algorithm and proves that the algorithm can be used in identifying the key actors in complex international crises. Originality/value The importance of the study lies in two main points. It proposes a new algorithm that mixes NLP, network extraction from textual unstructured data and DNA to understand and monitor changes occurring in a complex international crisis. It applies the proposed algorithm on the Syrian crisis as a case study to identify the key actors and hence validate the proposed algorithm.

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Analysis and Visualization of Dynamic Networks

Cited by 7 publications

References 24 publications

Social Media and Journalism

Social Media and Journalism

A Taxonomy and Survey of Dynamic Graph Visualization

Identifying key actors in an international crisis using dynamic network analysis

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