Influence et contagion
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Influence et contagion
L'influence et la contagion dans la cyberculture
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#Culturegraphy: the Cultural Influences and References between Movies | #DH #influence #dataviz

#Culturegraphy: the Cultural Influences and References between Movies | #DH #influence #dataviz | Influence et contagion | Scoop.it
luiy's insight:

Culturegraphy [culturegraphy.com], developed by "Information Model Maker" Kim Albrecht reveals represent complex relationships of over 100 years of movie references.

 

Movies are shown as unique nodes, while their influences are depicted as directed edges. The color gradients from blue to red that originate in the1980s denote the era of postmodern cinema, the era in which movies tend to adapt and combine references from other movies.

 

Although the visualizations look rather minimalistic at first sight, their interactive features are quite sophisticated and the resulting insights are naturally interesting. Therefore, do not miss out the explanatory movie below.

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GLEAMviz.org – The GLEAM Simulator system | #dataviz #complexity #prediction

GLEAMviz.org – The GLEAM Simulator system  | #dataviz #complexity #prediction | Influence et contagion | Scoop.it
luiy's insight:

The GLEAM Simulator system consists of the GLEAM Server and the GLEAMviz Client application.

 

The GLEAM Server uses GLEAM as the engine to perform the simulations. This server runs on high-performance computers managed by the GLEAM project.

 

The GLEAMviz Client is a desktop application through which users interact with the GLEAM Server. It provides a simple, intuitive and visual way to set up simulations, develop disease models, and evaluate simulation results using a variety of maps, charts and data analysis tools.

 

 

 Visualisation and analysis

 

GLEAMviz offers three types of visualization. The first shows the spread of the infection on a zoomable 2D map while charts show the number of new cases at various levels of detail.

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Mathematical Formulation of Multilayer Networks I #SNA #complexity #patterns

Mathematical Formulation of Multilayer Networks I #SNA #complexity #patterns | Influence et contagion | Scoop.it

Describing a social network based on a particular type of human social interaction, say, Facebook, is conceptually simple: a set of nodes representing the people involved in such a network, linked by their Facebook connections. But, what kind of network structure would one have if all modes of social interactions between the same people are taken into account and if one mode of interaction can influence another? Here, the notion of a “multiplex” network becomes necessary. Indeed, the scientific interest in multiplex networks has recently seen a surge. However, a fundamental scientific language that can be used consistently and broadly across the many disciplines that are involved in complex systems research was still missing. This absence is a major obstacle to further progress in this topical area of current interest. In this paper, we develop such a language, employing the concept of tensors that is widely used to describe a multitude of degrees of freedom associated with a single entity.

Our tensorial formalism provides a unified framework that makes it possible to describe both traditional “monoplex” (i.e., single-type links) and multiplex networks. Each type of interaction between the nodes is described by a single-layer network. The different modes of interaction are then described by different layers of networks. But, a node from one layer can be linked to another node in any other layer, leading to “cross talks” between the layers. High-dimensional tensors naturally capture such multidimensional patterns of connectivity. Having first developed a rigorous tensorial definition of such multilayer structures, we have also used it to generalize the many important diagnostic concepts previously known only to traditional monoplex networks, including degree centrality, clustering coefficients, and modularity.

We think that the conceptual simplicity and the fundamental rigor of our formalism will power the further development of our understanding of multiplex networks.


Via NESS
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A Look Inside Those 1.1 Million Open-Internet Comments | #datascience #complexity #SNA

A Look Inside Those 1.1 Million Open-Internet Comments | #datascience #complexity #SNA | Influence et contagion | Scoop.it
These cluster maps give us a two-dimensional look at the complex arguments Americans posted on the topic of net neutrality. One theme in the comments had to do with the American dream.
luiy's insight:

How To Read This Cluster Map

 

- Similar nodes typically cluster together and clusters are grouped by color

- Each node represents a news story; a node sized by degree represents number of connections (i.e., similarity) to other nodes

- Connections represent similar language used across nodes

- A node bridging two clusters can indicate a story that synthesizes multiple topics

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PLOS ONE #Complex systems articles | #ABM #netwoks #research

PLOS ONE #Complex systems articles | #ABM #netwoks #research | Influence et contagion | Scoop.it

PLOS ONE: an inclusive, peer-reviewed, open-access resource from the PUBLIC LIBRARY OF SCIENCE. Reports of well-performed scientific studies from all disciplines freely available to the whole world.


Via Bryan A. Knowles, Bernard Ryefield, Luciana Viter, Roger D. Jones, PhD
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