Intelligence
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 Rescooped by Jean-Michel Livowsky from Influence et contagion onto Intelligence

# Time varying networks and the weakness of strong ties | #patterns #rumor #SNA

In most social and information systems the activity of agents generates rapidly evolving time-varying networks. The temporal variation in networks' connectivity patterns and the ongoing dynamic processes are usually coupled in ways that still challenge our mathematical or computational modelling. Here we analyse a mobile call dataset and find a simple statistical law that characterize the temporal evolution of users' egocentric networks. We encode this observation in a reinforcement process defining a time-varying network model that exhibits the emergence of strong and weak ties. We study the effect of time-varying and heterogeneous interactions on the classic rumour spreading model in both synthetic, and real-world networks. We observe that strong ties severely inhibit information diffusion by confining the spreading process among agents with recurrent communication patterns. This provides the counterintuitive evidence that strong ties may have a negative role in the spreading of information across networks.

Via luiy
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# Intelligence

 Rescooped by Jean-Michel Livowsky from Intelligence stratégique et économique

## J'innove, donc je suis ! Visionnaires du XXIe siècle

Florin Paun- Edition L'Harmattan - Janvier 2014 - 202 PagesDes personnalités comme Edgar Morin et Lord Nicholas Stem ont accepté de rejoindre cette nouvelle approche dynamique de responsabilisation de chacun pour envisag

Via Aurélie Thev'
Corinne Chauffrut Werner 's curator insight,

Et dans la série de Florin Paun

TOUS ENTRE-PRENEURS ! La croissance du XXIe siècle à l'heure entrepreneurialesorti cet été et auquel j'ai eu le plaisir de contribuer http://www.editions-harmattan.fr/index.asp?navig=catalogue&obj=livre&no=43672

 Rescooped by Jean-Michel Livowsky from Intelligence stratégique et économique

## Le SYNFIE publie sa première lettre d’information

Disponible chaque trimestre, cette lettre d'information portera sur les activités du syndicat et sur l’actualité du secteur de l’intelligence économique. Le premier numéro met à l'honneur un agenda bien chargé autour de l'IE, ainsi que la mise en place d'un label qualité des prestataires en IE...

Via Aurélie Thev'
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 Rescooped by Jean-Michel Livowsky from Influence et contagion

## A taxonomy of #clustering procedures | #datascience

Via luiy
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 Rescooped by Jean-Michel Livowsky from e-Xploration

## Les #robots sur le Web social: état des lieux et #prospectives / via @LesDiplomates | #socialbots

Des robots avancés ont désormais infiltré les réseaux sociaux et peuvent interagir et tromper les êtres humains. Quelle impact sur les métiers du numérique?

Via luiy
luiy's curator insight,

De fait, les "bots" ne sont plus un épiphénomène, mais participent pleinement au fonctionnement d’Internet. Mais au-delà des classiquescrawlers bots, l’apparition de programmes automatiques plus ou moins raffinés sur le Web social pose indubitablement des questions d’ordre éthique, juridique et, surtout, stratégique.

Etat des lieux des robots à l’heure actuelle

A l’origine, les robots étaient des programmes informatiques censés effectuer des tâches répétitives, simples et automatisées, à un degré de fréquence plus ou moins élevé, avec le minimum d’implication.

Mais ces programmes ont gagné en raffinement à mesure qu’ils s’attaquaient aux réseaux sociaux. Désormais, des "socialbots" avancés ont infiltré Twitter et d’autres réseaux sociaux et sont en mesure de tromper les êtres humains. Si votre première pensée consiste à croire qu’un robot est facilement repérable et qu’il n’est pas très sophistiqué, vous êtes dans l’erreur. Un groupe de chercheurs brésiliens a récemment démontré que non seulement les robots étaient en mesure de pénétrer et stimuler des communautés, mais ils pouvaient également altérer leurs opinions et devenir des influenceurs.

 Rescooped by Jean-Michel Livowsky from Peer2Politics

## Knowledge Sharing Tools and Methods Toolkit - Social Network Analysis

"Social network analysis is the mapping and measuring of relationships and flows between people, groups, organisations, computers or other information/knowledge processing entities." (Valdis Krebs, 2002). Social Network Analysis (SNA) is a method for visualizing our people and connection power, leading us to identify how we can best interact to share knowledge.

Via jean lievens
luiy's curator insight,

When to use:Visualize relationships within and outside of the organization.Facilitate identification of who knows who and who might know what - teams and individuals playing central roles - thought leaders, key knowledge brokers, experts, etc.Identify isolated teams or individuals and knowledge bottlenecks.Strategically work to improve knowledge flows.Accelerate the flow of knowledge and information across functional and organisational boundaries.Improve the effectiveness of formal and informal communication channels.Raise awareness of the importance of informal networks.

Karen du Toit's curator insight,

A great wiki to check out about social network analysis

Provides links to a variety of social network analysis tools

 Rescooped by Jean-Michel Livowsky from Intelligence stratégique et économique

## Les panneaux solaires du futur seront transparents

Belle avancéeSCIENCE - Produire de l'énergie solaire avec votre téléphone ou grâce au pare-brise de votre voiture? Ce n'est pas de la science-fiction. Des chercheurs de l'Université du Michigan ont réussi à mettre ...

Via Aurélie Thev'
No comment yet.
 Rescooped by Jean-Michel Livowsky from Complex World

## Physicists eye neural fly data, find formula for Zipf's law

Physicists have identified a mechanism that may help explain Zipf's law – a unique pattern of behavior found in disparate systems, including complex biological ones. The journal Physical Review Letters is publishing their mathematical models, which demonstrate how Zipf's law naturally arises when a sufficient number of units react to a hidden variable in a system.

Via Claudia Mihai
Jean-Michel Livowsky's curator insight,

Maintenant, on sait pourquoi les terroristes du hamaSS volent, et surtout comment.

 Rescooped by Jean-Michel Livowsky from Complex World

## Sand Pile Model of the Mind Grows in Popularity

Support is growing for a decades-old physics idea suggesting that localized episodes of disordered brain activity help keep the overall system in healthy balance

Via Claudia Mihai
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 Rescooped by Jean-Michel Livowsky from e-Xploration

## 2014 #Ebola Outbreak: Worldwide Air Transportation and Relative Import #Risk | #dataviz

Via luiy
luiy's curator insight,
The Nodes: Nodes in the network represent the largest 1227 airports in the worldwide air-transportation network (WAN) comprising approx. 95% of the entire global air traffic. The dataset used in our computational models contains more than 4000 airports, a total passenger flux of more than 3 billion passengers/year. Node size quantifies the capacity (size) of an airport. Colors correspond to geographical regions. Hover over a node for an additional info pop-up.
 Rescooped by Jean-Michel Livowsky from Intelligence stratégique et économique

## Les pays développés ne sont plus qu'à moitié riche

Les pays développés produisent désormais moins de 50% de la richesse mondiale, dépassés par la poussée économique des grands pays émergents... et des pays en développement.

Via Aurélie Thev'
Jean-Michel Livowsky's insight:

Voilà qui peut-être explique certaines choses !

No comment yet.
 Rescooped by Jean-Michel Livowsky from Complex World

## Physicists eye neural fly data, find formula for Zipf's law

Physicists have identified a mechanism that may help explain Zipf's law – a unique pattern of behavior found in disparate systems, including complex biological ones. The journal Physical Review Letters is publishing their mathematical models, which demonstrate how Zipf's law naturally arises when a sufficient number of units react to a hidden variable in a system.

Via Claudia Mihai
Jean-Michel Livowsky's insight:

Maintenant, on sait pourquoi les terroristes du hamaSS volent, et surtout comment.

No comment yet.
 Rescooped by Jean-Michel Livowsky from Intelligence stratégique et économique

## Le vertige technologique masque un déficit majeur d'Innovation organisationnelle

Les objets technologiques mettent parfois des années pour révéler les domaines sur lesquels ils agiront et quelles nouvelles applications ils (...)

Via Aurélie Thev'
Stéphane NEREAU's curator insight,

 Rescooped by Jean-Michel Livowsky from Complex World

## Connecting Core Percolation and Controllability of Complex Networks

Core percolation is a fundamental structural transition in complex networks related to a wide range of important problems. Recent advances have provided us an analytical framework of core percolation in uncorrelated random networks with arbitrary degree distributions. Here we apply the tools in analysis of network controllability. We confirm analytically that the emergence of the bifurcation in control coincides with the formation of the core and the structure of the core determines the control mode of the network. We also derive the analytical expression related to the controllability robustness by extending the deduction in core percolation. These findings help us better understand the interesting interplay between the structural and dynamical properties of complex networks.

Via Shaolin Tan, A. J. Alvarez-Socorro, Tim Williamson, NESS, Claudia Mihai
Sibout Nooteboom's curator insight,

 Rescooped by Jean-Michel Livowsky from Influence et contagion

## How Videos Go #Viral part | / #metrics #SNA #contagion

Via luiy
luiy's curator insight,

This is a big post with a lot of variables and data. So let’s recap on what we’re saying overall. How do viral videos spread socially?

We can see there are 2 broad patterns of content diffusion. One model we call “spike” – the sudden ‘explosion’ of sharing activity – and the other we call “growth”, where popularity is a slower and steadier grower.  The metrics we’ve discussed, such as velocity, variability and social currency, provide a way to identify which kind of virality you’re looking:

http://www.facegroup.com/blog/how-videos-go-viral.html

 Rescooped by Jean-Michel Livowsky from Intelligence stratégique et économique

## La Suisse veut investir des millions pour des nouveaux moyens d'espionnage

Le Conseil fédéral veut développer des moyens plus conséquents pour écouter les conversations téléphoniques des suspects dans les enquêtes judiciaires.

Via Aurélie Thev'
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 Rescooped by Jean-Michel Livowsky from Influence et contagion

## Strongly Connected Component | #SNA #datascience

Via luiy
luiy's curator insight,

Graph connectivity is of special interest in networking, search, shortest path and many other applications.

Strongly connected directed graph has a path from all vertices to all vertices.

Strongly connected components (SCC) are the strongly connected subgraphs.

- abe, fg, cd and h are the strongly connected subgraphs of G.

 Rescooped by Jean-Michel Livowsky from Peer2Politics

## Knowledge Sharing Tools and Methods Toolkit - Social Network Analysis

"Social network analysis is the mapping and measuring of relationships and flows between people, groups, organisations, computers or other information/knowledge processing entities." (Valdis Krebs, 2002). Social Network Analysis (SNA) is a method for visualizing our people and connection power, leading us to identify how we can best interact to share knowledge.

Via jean lievens
luiy's curator insight,

When to use:Visualize relationships within and outside of the organization.Facilitate identification of who knows who and who might know what - teams and individuals playing central roles - thought leaders, key knowledge brokers, experts, etc.Identify isolated teams or individuals and knowledge bottlenecks.Strategically work to improve knowledge flows.Accelerate the flow of knowledge and information across functional and organisational boundaries.Improve the effectiveness of formal and informal communication channels.Raise awareness of the importance of informal networks.

Karen du Toit's curator insight,

A great wiki to check out about social network analysis

Provides links to a variety of social network analysis tools

 Rescooped by Jean-Michel Livowsky from Complex World

## Punctuated Equilibrium in the Large Scale Evolution of Programming Languages

The analogies and differences between biological and cultural evolution have been explored by evolutionary biologists, historians, engineers and linguists alike. Two well known domains of cultural change are language and technology. Both share some traits relating the evolution of species, but technological change is very difficult to study. A major challenge in our way towards a scientific theory of technological evolution is how to properly define evolutionary trees or clades and how to weight the role played by horizontal transfer of information. Here we study the large scale historical development of programming languages, which have deeply marked social and technological advances in the last half century. We analyse their historical connections using network theory and reconstructed phylogenetic networks. Using both data analysis and network modelling, it is shown that their evolution is highly uneven, marked by innovation events where new languages are created out of improved combinations of different structural components belonging
to previous languages. These radiation events occur in a bursty pattern and are tied to novel technological and social niches. The method can be extrapolated to other systems and consistently captures the major classes of languages and the widespread horizontal design exchanges, revealing a punctuated evolutionary path.

Via Claudia Mihai
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 Rescooped by Jean-Michel Livowsky from Complex World

## How bird flocks are like liquid helium

Mathematical model shows how hundreds of starlings coordinate their movements in flight.

A flock of starlings flies as one, a spectacular display in which each bird flits about as if in a well-choreographed dance. Everyone seems to know exactly when and where to turn. Now, for the first time, researchers have measured how that knowledge moves through the flock—a behavior that mirrors certain quantum phenomena of liquid helium.

Via Claudia Mihai
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 Rescooped by Jean-Michel Livowsky from Complex World

## Scaling of Chaos versus Periodicity: How Certain is it that an Attractor is Chaotic?

A small perturbation in a system's parameter can convert its attractor from chaotic to periodic, where the probability of obtaining a chaotic regime scales as a power law with respect to the perturbation size.

Via Claudia Mihai
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 Rescooped by Jean-Michel Livowsky from e-Xploration

## Israel, Gaza, #War & Data | #SNA #socialmedia

social networks and the art of personalizing propaganda

Via luiy
luiy's curator insight,

It’s hard to shake away the utterly depressing feeling that comes with news coverage these days. IDF and Hamas are at it again, a vicious cycle of violence, but this time it feels much more intense. While war rages on the ground in Gaza and across Israeli skies, there’s an all-out information war unraveling in social networked spaces.

Not only is there much more media produced, but it is coming at us at a faster pace, from many more sources. As we construct our online profiles based on what we already know, what we’re interested in, and what we’re recommended, social networks are perfectly designed to reinforce our existing beliefs. Personalized spaces, optimized for engagement, prioritize content that is likely to generate more traffic; the more we click, share, like, the higher engagement tracked on the service. Content that makes us uncomfortable, is filtered out.

 Rescooped by Jean-Michel Livowsky from Complex World

## Computational Linguistics of Twitter Reveals the Existence of Global Superdialects

The first study of dialects on Twitter reveals global patterns that have never been observed before.

Via Claudia Mihai
Jean-Michel Livowsky's insight:

Les bases d'un meta-langage universel ?

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 Rescooped by Jean-Michel Livowsky from Complex World

## Competitive Dynamics on Complex Networks

We consider a dynamical network model in which two competitors have fixed and different states, and each normal agent adjusts its state according to a distributed consensus protocol. The state of each normal agent converges to a steady value which is a convex combination of the competitors' states, and is independent of the initial states of agents. This implies that the competition result is fully determined by the network structure and positions of competitors in the network. We compute an Influence Matrix (IM) in which each element characterizing the influence of an agent on another agent in the network. We use the IM to predict the bias of each normal agent and thus predict which competitor will win. Furthermore, we compare the IM criterion with seven node centrality measures to predict the winner. We find that the competitor with higher Katz Centrality in an undirected network or higher PageRank in a directed network is most likely to be the winner. These findings may shed new light on the role of network structure in competition and to what extent could competitors adjust network structure so as to win the competition.

Via Claudia Mihai
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 Rescooped by Jean-Michel Livowsky from Complex World

## Hidden scaling patterns and universality in written communication

The temporal statistics exhibited by written correspondence appear to be media dependent, with features which have so far proven difficult to characterize. We explain the origin of these difficulties by disentangling the role of spontaneous activity from decision-based prioritizing processes in human dynamics, clocking all waiting times through each agent's proper time'' measured by activity. This unveils the same fundamental patterns in written communication across all media (letters, email, sms), with response times displaying truncated power-law behavior and average exponents near -${}\frac{3}{2}$. When standard time is used, the response time probabilities are theoretically predicted to exhibit a bimodal character, which is empirically borne out by our newly collected years-long data on email. These perspectives on the temporal dynamics of human correspondence should aid in the analysis of interaction phenomena in general, including resource management, optimal pricing and routing, information sharing, and emergency handling.

Via Claudia Mihai
No comment yet.
 Rescooped by Jean-Michel Livowsky from Intelligence stratégique et économique

## Le vertige technologique masque un déficit majeur d'Innovation organisationnelle

Les objets technologiques mettent parfois des années pour révéler les domaines sur lesquels ils agiront et quelles nouvelles applications ils (...)

Via Aurélie Thev'
Stéphane NEREAU's curator insight,