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Rescooped by Jean-Michel Livowsky from Semantic Sphere
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Les Mots du Web, expliqués par Pierre Lévy by franceculture

Les Mots du Web, expliqués par Pierre Lévy by franceculture | Intelligence | Scoop.it
TOUCH cette image pour découvrir son histoire. Marquage d'images développé par ThingLink

Via Pierre Levy
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Claire-Anne's curator insight, March 23, 3:43 PM

Quelques mots du web expliqués par Pierre Lévy

Rescooped by Jean-Michel Livowsky from Influence et contagion
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Modeling #Emotion #Influence from Images in Social Networks | #SNA

Modeling #Emotion #Influence from Images in Social Networks | #SNA | Intelligence | Scoop.it

Via luiy
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luiy's curator insight, January 21, 9:37 AM

Images become an important and prevalent way to express users' activities, opinions and emotions. In a social network, individual emotions may be influenced by others, in particular by close friends. We focus on understanding how users embed emotions into the images they uploaded to the social websites and how social influence plays a role in changing users' emotions. We first verify the existence of emotion influence in the image networks, and then propose a probabilistic factor graph based emotion influence model to answer the questions of "who influences whom". Employing a real network from Flickr as experimental data, we study the effectiveness of factors in the proposed model with in-depth data analysis. Our experiments also show that our model, by incorporating the emotion influence, can significantly improve the accuracy (+5%) for predicting emotions from images. Finally, a case study is used as the anecdotal evidence to further demonstrate the effectiveness of the proposed model.

Rescooped by Jean-Michel Livowsky from Influence et contagion
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Competition among #memes in a world with limited attention | #SNA #ABM #prediction

Competition among #memes in a world with limited attention | #SNA #ABM #prediction | Intelligence | Scoop.it
The wide adoption of social media has increased the competition among ideas for our finite attention. We employ a parsimonious agent-based model to study whether such a competition may affect the popularity of different memes, the diversity of information we are exposed to, and the fading of our collective interests for specific topics. Agents share messages on a social network but can only pay attention to a portion of the information they receive. In the emerging dynamics of information diffusion, a few memes go viral while most do not. The predictions of our model are consistent with empirical data from Twitter, a popular microblogging platform. Surprisingly, we can explain the massive heterogeneity in the popularity and persistence of memes as deriving from a combination of the competition for our limited attention and the structure of the social network, without the need to assume different intrinsic values among ideas.

Via luiy
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luiy's curator insight, February 22, 8:06 AM

Here we outline a number of empirical findings that motivate both our question and the main assumptions behind our model. We then describe the proposed agent-based toy model of meme diffusion and compare its predictions with the empirical data. Finally we show that the social network structure and our finite attention are both key ingredients of the diffusion model, as their removal leads to results inconsistent with the empirical data.

 

-----------------------------

Limited attention


We first explore the competition among memes. In particular, we test the hypothesis that the attention of a user is somewhat independent from the overall diversity of information discussed in a given period. Let us quantify the breadth of attention of a user through Shannon entropy S = −Σi f(i) log f(i) where f(i) is the proportion of tweets generated by the user about meme i. Given a user who has posted n messages, her entropy can be as small as 0, if all of her posts are about the same meme; or as large as log n if she has posted a message about each of n different memes. We can measure the diversity of the information available in the system analogously, defining f(i) as the proportion of tweets about meme i across all users. Note that these entropy-based measures are subject to the limits of our operational definition of a meme; finer or coarser definitions would yield different values.

 

John Caswell's curator insight, March 2, 8:23 AM

Very intetesting! Attention spans!

Rescooped by Jean-Michel Livowsky from Digital Humanities for beginners
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The Potential of Social Network Analysis in Intelligence

The Potential of Social Network Analysis in Intelligence | Intelligence | Scoop.it
Within its limits, SNA can be applied to identify individuals or organizations within a network, generate new leads and simulate flows of information or money throughout a network.

Via Pierre Levy
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luiy's curator insight, January 17, 8:53 AM

Social Network Analysis, as an analytic method, has inarguable applicability to the field of intelligence and is progressively reshaping the analytic landscape in terms of how analysts understand networks. For example, analysts currently use SNA to identify key people in an organization or social network, develop a strategic agent network, identify new agents and simulate information flows through a network. Beyond this, SNA can be easily combined with other analytic practices such as Geographic Information Systems (GIS), gravity model analysis or Intelligence Preparation of the Battlefield (IPB) to create robust, predictive analyses.

Rescooped by Jean-Michel Livowsky from Complex World
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Do the Rich Get Richer? An Empirical Analysis of the Bitcoin Transaction Network

Do the Rich Get Richer? An Empirical Analysis of the Bitcoin Transaction Network | Intelligence | Scoop.it

The possibility to analyze everyday monetary transactions is limited by the scarcity of available data, as this kind of information is usually considered highly sensitive. Present econophysics models are usually employed on presumed random networks of interacting agents, and only some macroscopic properties (e.g. the resulting wealth distribution) are compared to real-world data. In this paper, we analyze Bitcoin, which is a novel digital currency system, where the complete list of transactions is publicly available. Using this dataset, we reconstruct the network of transactions and extract the time and amount of each payment. We analyze the structure of the transaction network by measuring network characteristics over time, such as the degree distribution, degree correlations and clustering. We find that linear preferential attachment drives the growth of the network. We also study the dynamics taking place on the transaction network, i.e. the flow of money. We measure temporal patterns and the wealth accumulation. Investigating the microscopic statistics of money movement, we find that sublinear preferential attachment governs the evolution of the wealth distribution. We report a scaling law between the degree and wealth associated to individual nodes.

 


Via Claudia Mihai
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Eli Levine's curator insight, February 12, 11:25 PM

See, wealth compounds wealth.

Proven again.
...
So long as you have unequal ends, you're going to have unequal beginnings.

Unequal beginnings means unequal opportunities.

And, if research into child development has shown anything, it's that these benefits of being wealthy effect the development of our children mentally and physically in more profound ways than just economic advantage.

There is no equality of opportunity in this present economic system.

Therefore, let's stop burning ourselves out for nothing and fight for something that actually is of value to us, as human beings.

Think about it.

Rescooped by Jean-Michel Livowsky from Self-organizing and Systems Mapping
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Self-Organizing Networked Systems: So when do we call a system self-organizing?

Self-Organizing Networked Systems: So when do we call a system self-organizing? | Intelligence | Scoop.it
Self-Organizing Networked Systems -- A new paradigm for controlling networked systems

Via june holley
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luiy's curator insight, February 12, 7:28 AM

- A self-organizing system (SOS) consists of a set of entities that obtains an emerging global system behavior via local interactions without centralized control.
(from Research Days'08, see [IWSOS:2008]))

- Self-organization is the process where a structure or pattern appears in a system without a central authority or external element imposing it through planning. (Wikipedia)

- A self-organizing system is a system that changes its basic structure as a function of its experience and environment. (Farley and Clark 1954)

- Are they really refering to the same thing? So be warned, when a discussion heads towards the definition of self-organization!

Liz Rykert's curator insight, February 14, 9:12 PM

Culture in an organization feels like it results from self-organizing patterns of relating. Here is one of three refs within the article - it is short and worth the read: A self-organizing system (SOS) consists of a set of entities that obtains an emerging global system behavior via local interactions without centralized control.
(from Research Days'08, see [IWSOS:2008]))

Leadership Learning Community's curator insight, February 15, 1:07 PM

Another important concept to help structure leaders' collaborative learning.

Rescooped by Jean-Michel Livowsky from Intelligence
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To Foster Your Creativity, Don't Learn To Code; Learn To Paint

To Foster Your Creativity, Don't Learn To Code; Learn To Paint | Intelligence | Scoop.it
The best way to foster innovation and creativity is to study and seriously practice the arts.

Via Claudia Mihai, Jean-Michel Livowsky
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Jean-Michel Livowsky's curator insight, February 6, 6:44 AM

Einstein, franchement, était d'une nullité crasse au violon. Heureusement, il était plus physique, comme garçon.

Rescooped by Jean-Michel Livowsky from Homo Agilis (Collective Intelligence, Agility and Sustainability : The Future is already here)
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Accelerate - leveraging collective intelligence...

Accelerate - leveraging collective intelligence... | Intelligence | Scoop.it

Via Claude Emond
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Rescooped by Jean-Michel Livowsky from Homo Agilis (Collective Intelligence, Agility and Sustainability : The Future is already here)
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Network Science Book - you can download the book here

Network Science Book - you can download the book here | Intelligence | Scoop.it
The power of network science, the beauty of network visualization.

Via Claude Emond
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Claude Emond's comment, February 8, 8:27 PM
Bienvenu Luis
Rescooped by Jean-Michel Livowsky from Commerce Connecté
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Responsive Design : points forts et points faibles

Responsive Design : points forts et points faibles | Intelligence | Scoop.it
Points forts et points faibles du responsive design

Via TROUVE LIONEL
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Rescooped by Jean-Michel Livowsky from Complex World
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Hedonometer

Hedonometer | Intelligence | Scoop.it

Hedonometer.org is an instrument that measures the happiness of large populations in real time.


Via Claudia Mihai
Jean-Michel Livowsky's insight:

La mesure électronique du bonheur et du bien-être... Le Bhoutan et le «bonheur national brut»  n'ont qu'a bien se tenir, il est vrai que le concept a été enterré depuis peu...

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luiy's curator insight, February 5, 6:16 AM
Happiness

It’s what most people say they want. So how do we know how happy people are? You can’t improve or understand what you can’t measure. In a blow to happiness, we’re very good at measuring economic indices and this means we tend to focus on them. With hedonometer.org we’ve created an instrument that measures the happiness of large populations in real time.

 

Our hedonometer is based on people’s online expressions, capitalizing on data-rich social media, and we’re measuring how people present themselves to the outside world. For our first version of hedonometer.org, we’re using Twitter as a source but in principle we can expand to any data source in any language (more below). We’ll also be adding an API soon.

 

So this is just a start — we invite you to explore the Twitter time series and let us know what you think.

Eli Levine's curator insight, February 5, 11:03 AM

Isn't this what we're all looking for?

Happiness, health and well being?

 

There's a very good reason how Thomas Jefferson said "life, liberty and the pursuit of happiness", rather than property.

 

Yet we've confused the two to such an extent that we end up having neither on the general, collective sense (which basically boils down to being the majority of the individuals living in a society).

 

Think about it.

Rescooped by Jean-Michel Livowsky from Social Network Analysis Applications
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The Network Secrets of Great Change Agents

The Network Secrets of Great Change Agents | Intelligence | Scoop.it
Business management magazine, blogs, case studies, articles, books, and webinars from Harvard Business Review, addressing today's topics and challenges in business management.

Via Premsankar Chakkingal
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Premsankar Chakkingal's curator insight, February 1, 12:54 AM
Change is hard, especially at large organizations. But some leaders do succeed at transforming their workplaces. How? The secret lies in how they understand and mobilize their informal networks:
luiy's curator insight, February 4, 3:55 AM

In tracking 68 of these initiatives for one year after their inception, we discovered some striking predictors of change agents’ success. The short story is that their personal networks—their relationships with colleagues—were critical. More specifically, we found that:

 

1. Change agents who were central in the organization’s informal network had a clear advantage, regardless of their position in the formal hierarchy.

 

2. People who bridged disconnected groups and individuals were more effective at implementing dramatic reforms, while those with cohesive networks were better at instituting minor changes.

 

3. Being close to “fence-sitters,” who were ambivalent about a change, was always beneficial. But close relationships with resisters were a double-edged sword: Such ties helped change agents push through minor initiatives but hindered major change attempts.

 

Rescooped by Jean-Michel Livowsky from Intelligence stratégique et économique
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Quand la croyance devient de l’information

Quand la croyance devient de l’information | Intelligence | Scoop.it
Une étude vaguement menée par deux étudiants de Princeton prédit la fin…

Via Aurélie Thev'
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Rescooped by Jean-Michel Livowsky from Influence et contagion
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Time varying networks and the weakness of strong ties | #patterns #rumor #SNA

Time varying networks and the weakness of strong ties | #patterns #rumor #SNA | Intelligence | Scoop.it

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.


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Network Science Book - you can download the book here | #SNA

Network Science Book - you can download the book here | #SNA | Intelligence | Scoop.it
The power of network science, the beauty of network visualization.

Via Claude Emond, luiy
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Claude Emond's comment, February 8, 8:27 PM
Bienvenu Luis
Rescooped by Jean-Michel Livowsky from Big Data, Cloud and Social everything
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Pierre Lévy, l'intelligence collective - Information - France Culture

Pierre Lévy, l'intelligence collective - Information - France Culture | Intelligence | Scoop.it

Via Pierre Levy
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Claude Emond's curator insight, February 17, 8:13 AM

Entrevue (podcast) du 15 février 2014 sur France Culture. Pierre Levy nous parle de l'état de l'intellingence collective. à écouter sans faute.

 

thierrydenys's curator insight, February 21, 3:16 PM

Un summum, une merveille....Des pépites en pagaille, une vision hors du commun, des liens avec la sémantique générale de Alfred KORZYBSKI (1937, un autre génie...), bref l'avenir est pensé ici avec une puissance assez impressionnante : 

thierrydenys's curator insight, February 21, 3:17 PM

Un summum, une merveille....Des pépites en pagaille, une vision hors du commun, des liens avec la sémantique générale de Alfred KORZYBSKI (1937, un autre génie...), bref l'avenir est pensé ici avec une puissance assez impressionnante :

Rescooped by Jean-Michel Livowsky from Digital Humanities for beginners
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archipress - Complexité(s). Le Mot du Siècle

archipress - Complexité(s). Le Mot du Siècle | Intelligence | Scoop.it
Archipress, agence d'informations scientifiques et culturelles

Ecoute la divine parole du savoir (slogan étudiant)

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Rescooped by Jean-Michel Livowsky from e-Xploration
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Learning for a #Change | The 10 #Challenges of Change

Learning for a #Change | The 10 #Challenges of Change | Intelligence | Scoop.it
Ten years ago, Peter Senge introduced the idea of the learning organization. Now he says that for big companies to change, we need to stop thinking...

Via luiy
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luiy's curator insight, February 11, 8:33 AM

Sidebar: The 10 Challenges of Change

 

In "The Dance of Change: The Challenges to Sustaining Momentum in Learning Organizations," Peter Senge and his colleagues identify 10 challenges of change. Grouped into three categories -- challenges of initiating change, challenges of sustaining momentum, and challenges of systemwide redesign and rethinking -- these 10 items amount to what the authors call "the conditions of the environment that regulate growth."

 

 

CHALLENGES OF INITIATING CHANGE

 

"We don't have time for this stuff!" People who are involved in a pilot group to initiate a change effort need enough control over their schedules to give their work the time that it needs.

 

"We have no help!" Members of a pilot group need enough support, coaching, and resources to be able to learn and to do their work effectively.

 

"This stuff isn't relevant." There need to be people who can make the case for change -- who can connect the development of new skills to the real work of the business.

 

"They're not walking the talk!" A critical test for any change effort: the correlation between espoused values and actual behavior.

 

 

CHALLENGES OF SUSTAINING MOMENTUM

 

"This stuff is . . ." Personal fear and anxiety -- concerns about vulnerability and inadequacy -- lead members of a pilot group to question a change effort.

 

"This stuff isn't working!" Change efforts run into measurement problems: Early results don't meet expectations, or traditional metrics don't calibrate to a pilot group's efforts.

 

"They're acting like a cult!" A pilot group falls prey to arrogance, dividing the company into "believers" and "nonbelievers."

 

 

CHALLENGES OF SYSTEMWIDE REDESIGN AND RETHINKING

 

"They . . . never let us do this stuff." The pilot group wants more autonomy; "the powers that be" don't want to lose control.

 

"We keep reinventing the wheel." Instead of building on previous successes, each group finds that it has to start from scratch.

 

"Where are we going?" The larger strategy and purpose of a change effort may be obscured by day-to-day activity. Big question: Can the organization achieve a new definition of success?

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Working Groups: the self-organising revolution | The Future of Occupy

Working Groups: the self-organising revolution | The Future of Occupy | Intelligence | Scoop.it

Via june holley
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MyKLogica's curator insight, February 18, 2:05 PM

Cuando el fenómeno de la holacracia se extiende a la sociedad.

Ali Anani's curator insight, February 24, 12:50 AM

Self-organizing or controlling? Which do you see fitter?

Nevermore Sithole's curator insight, March 14, 8:59 AM
Working Groups: the self-organising revolution | The Future of Occupy
Rescooped by Jean-Michel Livowsky from Data is big
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Top 11 Free Software for Text Analysis, Text Mining, Text Analytics - Predictive Analytics Today

Top 11 Free Software for Text Analysis, Text Mining, Text Analytics - Predictive Analytics Today | Intelligence | Scoop.it
Review of Top 11 Free Software for Text Analysis, Text Mining, Text Analytics ? KH Coder, Carrot2, GATE, tm, Gensim, Natural Language Toolkit, RapidMiner, Unstructured Information Management Architecture, OpenNLP, KNIME, Orange-Textable and LPU are some of the key vendors who provides text analytics software

Via ukituki
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Rescooped by Jean-Michel Livowsky from Homo Agilis (Collective Intelligence, Agility and Sustainability : The Future is already here)
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Le facteur humain au coeur de l'intelligence collective

Qu'est-ce que l'intelligence collective ? par Philippe Olivier Clément

Via Claude Emond
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Claude Emond's curator insight, February 6, 5:02 PM

Une évidence !!!

Rescooped by Jean-Michel Livowsky from Complex World
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Nonlinear Dynamics Analysis of a Self-Organizing Recurrent Neural Network: Chaos Waning

Nonlinear Dynamics Analysis of a Self-Organizing Recurrent Neural Network: Chaos Waning | Intelligence | Scoop.it

Self-organization is thought to play an important role in structuring nervous systems. It frequently arises as a consequence of plasticity mechanisms in neural networks: connectivity determines network dynamics which in turn feed back on network structure through various forms of plasticity. Recently, self-organizing recurrent neural network models (SORNs) have been shown to learn non-trivial structure in their inputs and to reproduce the experimentally observed statistics and fluctuations of synaptic connection strengths in cortex and hippocampus. However, the dynamics in these networks and how they change with network evolution are still poorly understood. Here we investigate the degree of chaos in SORNs by studying how the networks' self-organization changes their response to small perturbations. We study the effect of perturbations to the excitatory-to-excitatory weight matrix on connection strengths and on unit activities. We find that the network dynamics, characterized by an estimate of the maximum Lyapunov exponent, becomes less chaotic during its self-organization, developing into a regime where only few perturbations become amplified. We also find that due to the mixing of discrete and (quasi-)continuous variables in SORNs, small perturbations to the synaptic weights may become amplified only after a substantial delay, a phenomenon we propose to call deferred chaos.


Via Claudia Mihai
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Rescooped by Jean-Michel Livowsky from Complex World
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To Foster Your Creativity, Don't Learn To Code; Learn To Paint

To Foster Your Creativity, Don't Learn To Code; Learn To Paint | Intelligence | Scoop.it
The best way to foster innovation and creativity is to study and seriously practice the arts.

Via Claudia Mihai
Jean-Michel Livowsky's insight:

Einstein, franchement, était d'une nullité crasse au violon. Heureusement, il était plus physique, comme garçon.

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Rescooped by Jean-Michel Livowsky from Social Network Analysis Applications
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Twitter Trends Help Researchers Forecast Viral Memes

Twitter Trends Help Researchers Forecast Viral Memes | Intelligence | Scoop.it

What makes a meme— an idea, a phrase, an image—go viral? For starters, the meme must have broad appeal, so it can spread not just within communities of like-minded individuals but can leap from one community to the next. Researchers, by mining public Twitter data, have found that a meme's “virality” is often evident from the start. After only a few dozen tweets, a typical viral meme (as defined by tweets using a given hashtag) will already have caught on in numerous communities of Twitter users. In contrast, a meme destined to peter out will resonate in fewer groups.

 


Via Claudia Mihai, ukituki, Premsankar Chakkingal
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june holley's curator insight, January 23, 8:31 AM

Some important ideas here for people interested in change.

Premsankar Chakkingal's curator insight, January 30, 8:58 AM

Forecasting the Future Twitter Trends in hashtags

Christian Verstraete's curator insight, February 3, 4:48 AM

Twitter, what happens when things go viral?

Rescooped by Jean-Michel Livowsky from E-Learning-Inclusivo (Mashup)
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Causerie-débat sur IEML et les écosystèmes d'idées @Plevy

Causerie-débat sur IEML et les écosystèmes d'idées @Plevy | Intelligence | Scoop.it
Causerie-débat de Pierre Lévy sur le futur de la communication numérique Date: le 15 février à 18h Lieu: Paris, 18 rue Hermel 75018, Métro Jules Joffrin Hashtag: #plevyaparis THÈME Le jour va bient...

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Rodrigo Mesquita's curator insight, February 4, 8:08 AM

não morro de amores por nenhuma ferramenta/plataforma da internet. ignorá-las ou considerá-las caminhos para fazer amigos é querer ficar fora do mercado, fenecer. atuar hoje como profissional de informação, comunicação e articulação - a missão dos jornalistas - exige um bom conhecimento da rede e seu ecossistema, que evolui todos os dias.