Networks and Big Data
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Networks and Big Data
Networks are everywhere... but we are still unaware of their presence and importance
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Metaphor map charts the images that structure our thinking

Metaphor map charts the images that structure our thinking | Networks and Big Data | Scoop.it
Metaphor is not the sole preserve of Shakespearean scholarship or high literary endeavour but has governed how we think about and describe our daily lives for centuries, according to researchers at Glasgow University.

Experts have now created the world’s first online Metaphor Map, which contains more than 14,000 metaphorical connections sourced from 4m pieces of lexical data, some of which date back to 700AD.

While it is impossible to pinpoint the oldest use of metaphor in English, because some may have been adopted from earlier languages such as Germanic, the map reveals that the still popular link between sheep and timidity dates back to Old English. Likewise, we do not always recognise modern use of metaphor: for example, the word “comprehend” comes from Latin, where it meant to physically grasp an object.

The three-year-long project to map the use of metaphor across the entire history of the English language, undertaken by researchers at the School of Critical Studies, was based on data contained in the Historical Thesaurus of English, which spans 13 centuries.

Dr Wendy Anderson, the project’s principal investigator, said that the findings supported the view that metaphor is pervasive in language and is also a major mechanism of meaning-change.

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Study: Polarization in Congress is worsening… and it stifles innovation

Study: Polarization in Congress is worsening… and it stifles innovation | Networks and Big Data | Scoop.it
A new study confirms quantitatively that partisan disagreements in the U.S. Congress are worsening and that polarization is harmful to ...
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CM Winter Lab 2015: Riflessioni su Grandi Dati, Complessità e... un po' di neuroni!

CM Winter Lab 2015: Riflessioni su Grandi Dati, Complessità e... un po' di neuroni! | Networks and Big Data | Scoop.it
CM Winter Lab 2015 - Presentazione di Matteo Busanelli all'Open Mind Lab: "Riflessioni su Grandi Dati, Complessità e... un po' di neuroni!" In conclusione al Complexity Management Winter Lab che si...
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Data, data everywhere

Data, data everywhere | Networks and Big Data | Scoop.it
All these examples tell the same story: that the world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account.
Complexity Institute's insight:

An article dated 2010, but still interesting.

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How big data is beginning to change how medicine works

How big data is beginning to change how medicine works | Networks and Big Data | Scoop.it

The face of medical care is rapidly changing thanks to major advancements in the capture, proliferation, and analysis of medical data. Technologies like the electronic health records (EHRs) and personal health records (PHRs) are drastically improving the way data is aggregated and shared.

 

Now the hope is that big data analytics will help to make sense of seemingly endless streams of medical information.


As many doctors are painfully aware, outcome-oriented care is no longer a buzzword but a reality. The Center for Medicare and Medicaid Services has started to implement a program where payments are based on the ability of providers to meet key National Quality Strategy Domains (e.g. care criteria). Public payers are testing this new methodology, and private payers are expected to soon follow.

 

These big data analytics applications can also be relevant for the FDA, which may want to see how drugs perform in a non-test environment to ensure the appropriate patient populations are receiving the drug. I also expect pharmaceutical companies to actively scour this data to track drug efficacy post-release or identify markets that could “benefit” from increased penetration.

 

I am eager to see how the data evolution improves outcomes for doctors and patients.

 

 

more at http://venturebeat.com/2014/10/16/how-big-data-is-beginning-to-change-how-medicine-works/ ;
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From Crystal Ball to Magic Wand: The New World Order in Times of Digital Revolution - YouTube

From Crystal Ball to Magic Wand: The New World Order in Times of Digital Revolution. Dirk Helbing, ETH Zurich. Talk delivered via skype on March 24, 2014, to...
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Dirk Helbing: Keynote: How to Create a Better World - YouTube

http://2014.sotm-eu.org/en/slots/28 Planetary Nervous System, Global Participatory Platform, Social Information Technologies: How to Create a Better World It...

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Luciano Lampi's curator insight, June 25, 2014 9:14 PM

an excellent link between the present and future under the point of view of complexity and ICT trends. 

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BIG DATA SOCIETY: Age of Reputation or Age of Discrimination?

If we want Big Data to create societal progress, more transparency and participatory opportunities are needed to avoid discrimination and ensure that they are used in a scientifically sound, trustable, and socially beneficial way.

Have you ever "enjoyed" an extra screening at the airport because you happened to sit next to someone from a foreign country? Have you been surprised by a phone call offering a special service or product, because you visited a certain webpage? Or do you feel your browser reads your mind? Then, welcome to the world of Big Data, which mines the tons of digital traces of our daily activities such as web searches, credit card transactions, GPS mobility data, phone calls, text messages, facebook profiles, cloud storage, and more. But are you sure you are getting the best possible product, service, insurance or credit contract? I am not.

 

BIG DATA SOCIETY: Age of Reputation or Age of Discrimination?

By Dirk Helbing

http://futurict.blogspot.ch/2014/09/big-data-society-age-of-reputation-or.html


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Eli Levine's curator insight, September 26, 2014 11:41 AM

Personally, I think it's more likely to increase peoples' abilities to make prejudicial choices about other people in addition to the actual technical advantages that this will bring about.  Thus, the universe doesn't so much as change for the better, but rather muddle on under the same basic principles.  We are only humans, after all.  Our descendants are not going to fall far from the tree and, unless something dramatic happens to our population and to the way that our people think and feel about themselves and our world (an x-event), there will likely only be questionable or low probability change as we settle into a kind of equilibrium, for better and for worse, that we may choose to die in, rather than evolve and make a change.

 

Thus, we're more than likely going to take a significant hit as a species, in spite of our abilities to avoid the problems in the first place.

 

Silly brains....

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What's the next window into our universe?

What's the next window into our universe? | Networks and Big Data | Scoop.it

Big Data is everywhere — even the skies. In an informative talk, astronomer Andrew Connolly shows how large amounts of data are being collected about our universe, recording it in its ever-changing moods. Just how do scientists capture so many images at scale? It starts with a giant telescope …

 

http://on.ted.com/c0RGN


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Origin and Structure of Dynamic Cooperative Networks

Origin and Structure of Dynamic Cooperative Networks | Networks and Big Data | Scoop.it
Societies are built on social interactions among individuals. Cooperation represents the simplest form of a social interaction: one individual provides a benefit to another one at a cost to itself. Social networks represent a dynamical abstraction of social interactions in a society. The behaviour of an individual towards others and of others towards the individual shape the individual's neighbourhood and hence the local structure of the social network. Here we propose a simple theoretical framework to model dynamic social networks by focussing on each individual's actions instead of interactions between individuals. This eliminates the traditional dichotomy between the strategy of individuals and the structure of the population and easily complements empirical studies. As a consequence, altruists, egoists and fair types are naturally determined by the local social structures, while globally egalitarian networks or stratified structures arise. Cooperative interactions drive the emergence and shape the structure of social networks.

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Study maps Twitter’s information ecosystem

Study maps Twitter’s information ecosystem | Networks and Big Data | Scoop.it
New research outlines the six types of communities on the social network and what that means for communication

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António F Fonseca's curator insight, March 1, 2014 7:59 AM

What community do you belong to?

Eli Levine's curator insight, March 1, 2014 4:24 PM

Indeed, we each live in our own world, not in the real world per se.

 

Some, however, have a more accurate understanding of the real world and are willing to acknowledge their shortcomings.

 

The others, who are less inclined to explore and are more focused on their own self-production, just happen to be known as conservative in our culture.  Hence, they area always hindered from perceiving the real world in the strictest of senses, and are not likely to change in light of new information received from the outside world.

 

Non-adapting humans will equal a dead and dying species.  It's a shame, though, that we can be dragged down by them for our lack of effective effort and action.

 

Sad.

 

Think about it.

Fàtima Galan's curator insight, March 3, 2014 2:44 AM

"The topographical "maps" of these communities, generated by Pew using the data visualization tool NodeXL, aren’t just maps of relationships. They represent the channels of information in Twitter’s vast ecosystem, the roads and throughways, stoops and street corners in each topical neighborhood where users congregate and swap news and anecdotes."

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Study uncovers six basic types of Twitter conversations

Study uncovers six basic types of Twitter conversations | Networks and Big Data | Scoop.it
Researchers say there are six structures for most conversations on Twitter, ranging from polarized debates to community clusters.

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Eli Levine's curator insight, February 23, 2014 1:05 PM

This is just plain interesting.

 

How often we talk, and how little we actually have to say.

 

Think about it.

António F Fonseca's curator insight, March 1, 2014 1:23 PM

I've already study this.

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Is this the real secret to Samsung’s success?

Is this the real secret to Samsung’s success? | Networks and Big Data | Scoop.it
Networking helps people progress at work and companies that build partnerships also do better, according to INSEAD academics.
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Ranking in interconnected multilayer networks reveals versatile nodes

Ranking in interconnected multilayer networks reveals versatile nodes | Networks and Big Data | Scoop.it

The determination of the most central agents in complex networks is important because they are responsible for a faster propagation of information, epidemics, failures and congestion, among others. A challenging problem is to identify them in networked systems characterized by different types of interactions, forming interconnected multilayer networks. Here we describe a mathematical framework that allows us to calculate centrality in such networks and rank nodes accordingly, finding the ones that play the most central roles in the cohesion of the whole structure, bridging together different types of relations. These nodes are the most versatile in the multilayer network. We investigate empirical interconnected multilayer networks and show that the approaches based on aggregating—or neglecting—the multilayer structure lead to a wrong identification of the most versatile nodes, overestimating the importance of more marginal agents and demonstrating the power of versatility in predicting their role in diffusive and congestion processes.

 

Ranking in interconnected multilayer networks reveals versatile nodes
Manlio De Domenico, Albert Solé-Ribalta, Elisa Omodei, Sergio Gómez & Alex Arenas

Nature Communications 6, Article number: 6868 http://dx.doi.org/10.1038/ncomms7868 ;


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Dmitry Alexeev's curator insight, May 6, 2015 10:03 AM

 insight on the networks

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CMWL 2015 - Intervista a Marisa Orlando e Simona Carta

CMWL 2015 - Intervista a Marisa Orlando e Simona Carta | Networks and Big Data | Scoop.it
Complexity Institute's insight:

“Come far capire la potenza delle reti neurali artificiali in maniera divertente? I giochi possono promuovere l’apprendimento e, soprattutto, simulano un contesto complesso all’interno di un’aula come questa… All’interno di questa stanza abbiamo simulato un po’ quello che accade anche all’interno di grandi organizzazioni.”

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Networks Reveal the Connections of Disease

Networks Reveal the Connections of Disease | Networks and Big Data | Scoop.it
Enormous databases of medical records have begun to reveal the hidden biological missteps that make us sick.

 

https://www.quantamagazine.org/20150129-networks-reveal-the-connections-of-disease/


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6 Ways Technology is Helping to Fight Ebola

6 Ways Technology is Helping to Fight Ebola | Networks and Big Data | Scoop.it
As Ebola continues to ravish Sierra Leone, Guinea and Liberia, people from all around the world are working together to stop the disease. In addition to the life saving work of medical staff, logisticians and community organizers, information and communication technology (ICT) is also playing a vital part in supporting their work. Below are six examples showing how ICT is already making a difference in the current Ebola crisis.

 

1. Tracing outbreaks with mapping and geolocation


2. Gathering Ebola information with digital data collection forms


3. Connecting the sick with their relatives using local Wi-Fi networks


4. Sharing and receiving Ebola information via SMS text messages


5. Mythbusting for diaspora communities via social media


6. Supporting translations of Ebola information remotely online


read more at http://techchange.org/2014/10/08/ebola-technology-ict/




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Lauren Silva's curator insight, October 8, 2014 8:06 PM

In an age where social media and technology affects the everyday human often, it is beneficial to view an article that details the benefits of technology in the world. This article doesn't specify how technology may stop ebola, it focuses more on how it can spread awareness, hope and understanding. The article doesn't pretend like the epidemic isn't happening, but instead focuses on the ups of what is. Family members can still communicate, awareness is spread, and information is reached all through technology.

nrip's comment, October 9, 2014 3:36 AM
@Lauren Silva Thanks for your comments
Eric Chan Wei Chiang's curator insight, October 10, 2014 2:31 AM

The spread of Ebola is a worrying trend http://sco.lt/8AK7FJ

which has gotten the attention of President Obama http://sco.lt/6yO8xd

 

WHO statements about the transmission of Ebola and the current status of the outbreak is scooped here: http://sco.lt/6Qpd3p

 

Innovative means of using technology to curb the spread is welcome indeed.

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Ebola Is Coming. A Travel Ban Won't Stop Outbreaks

Ebola Is Coming. A Travel Ban Won't Stop Outbreaks | Networks and Big Data | Scoop.it
Outbreaks begin with imported cases of Ebola, which has led Americans to ask: Why don't we just ban flights from Africa?
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Google Reveals ‘The Physical Web,’ A Project To Make Internet Of Things Interaction App-Less | TechCrunch

Google Reveals ‘The Physical Web,’ A Project To Make Internet Of Things Interaction App-Less | TechCrunch | Networks and Big Data | Scoop.it
Google's Scott Jenson, an interaction and UX designer who left the company previously, only to return to the Chrome team last November, has revealed a project..

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How Big The Internet Of Things Could Become

How Big The Internet Of Things Could Become | Networks and Big Data | Scoop.it

75 billion. That's the potential size of the Internet Things sector, which could become a multi-trillion dollar market by the end of the decade.

 

That's a very big number of devices that Morgan Stanley has extrapolated from a Cisco report that details how many devices will be connected to the Internet of Things by 2020. That's 9.4 devices for every one of the 8 billion people that's expected to be around in seven years.

 

To help put that into more perspective, back in Cisco also came out with the number of devices it thinks were connected to the Internet in 2012, a number Cisco's Rob Soderbery placed at 8.7 billion. Most of the devices at the time, he acknowledged were the PCs, laptops, tablets and phones in the world. But other types of devices will soon dominate the collection of the Internet of Things, such as sensors and actuators.

 

By the end of the decade, a nearly nine-fold increase in the volume of devices on the Internet of Things will mean a lot of infrastructure investment and market opportunities will available in this sector. And by "a lot," I mean ginourmous. In an interview with Barron's, Cisco CEO John Chambers figures that will translate to a $14-trillion industry.

 

Granted, Cisco has a lot of reasons to be bullish about the prospect of the Internet of Things: with product offerings in the router and switch space and a recent keen interest on building intelligent routing and application platforms right inside those devices, Cisco stands to gain a lot of business if it can get itself out in front of this newfangled Internet of Things.

 

It's not just Cisco talking up the Internet of Things: late last week, Morgan Stanley published a big 29-page research note on the topic that sought to at once define the Internet of Things and also quantify its size, growth and potential to make money.

 See also: Cisco Hearts Internet Of Things


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Complex network theory and the brain

Complex network theory and the brain | Networks and Big Data | Scoop.it

We have known for at least 100 years that a brain is organized as a network of connections between nerve cells. But in the last 10 years there has been a rapid growth in our capacity to quantify the complex topological pattern of brain connectivity, using mathematical tools drawn from graph theory.
Here we bring together articles and reviews from some of the world’s leading experts in contemporary brain network analysis by graph theory. The contributions are focused on three big questions that seem important at this stage in the scientific evolution of the field: How does the topology of a brain network relate to its physical embedding in anatomical space and its biological costs? How does brain network topology constrain brain dynamics and function? And what seem likely to be important future methodological developments in the application of graph theory to analysis of brain networks?
Clearer understanding of the principles of brain network organization is fundamental to understanding many aspects of cognitive function, brain development and clinical brain disorders. We hope this issue provides a forward-looking window on this fast moving field and captures some of the excitement of recent progress in applying the concepts of graph theory to measuring and modeling the complexity of brain networks.

 

Complex network theory and the brain
Issue compiled and edited by David Papo, Javier M. Buldú, Stefano Boccaletti and Edward T. Bullmore

http://rstb.royalsocietypublishing.org/site/2014/network.xhtml


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▶ Creating a Planetary Nervous System as a Citizen Web

This video has been presented at the Ubicomp 2014
Workshop on „The superorganism of massive collective wearables"

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Eli Levine's curator insight, September 19, 2014 9:26 AM

Interesting concept. I wonder if we already have this via the Internet. At any rate, I doubt that we'll be able to get it up and running in time to save anyone or anything. 

 

Nice thoughts. But nice thoughts don't really mean anything here in this universe. 

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Detecting Communities Based on Network Topology

Detecting Communities Based on Network Topology | Networks and Big Data | Scoop.it

Network methods have had profound influence in many domains and disciplines in the past decade. Community structure is a very important property of complex networks, but the accurate definition of a community remains an open problem. Here we defined community based on three properties, and then propose a simple and novel framework to detect communities based on network topology. We analyzed 16 different types of networks, and compared our partitions with Infomap, LPA, Fastgreedy and Walktrap, which are popular algorithms for community detection. Most of the partitions generated using our approach compare favorably to those generated by these other algorithms. Furthermore, we define overlapping nodes that combine community structure with shortest paths. We also analyzed the E. Coli. transcriptional regulatory network in detail, and identified modules with strong functional coherence.

  


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Ivon Prefontaine's curator insight, July 26, 2014 6:54 PM

Community is a more complex and organic organizing than teams. Teams are inherently hierarchical with predetermined goals. Communities are fluid and the goals are continuously being negotiated. Schools and classrooms are better served to be thought of as communities with overlapping qualities and permeable boundaries with other communities.

Eli Levine's curator insight, July 29, 2014 6:42 PM

A useful tool for policy making, because it helps identify communities and how they interact to form super-communities.

 

The essence of mapping the polity and the public, socially, economically, technologically, and infrastrucutrally.

 

Think about it.

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What Fuels the Most Influential Tweets?

What Fuels the Most Influential Tweets? | Networks and Big Data | Scoop.it
The number of followers you have and the exact wording matter less than you think. What makes a difference is having the right message for the right people.

Via luiy, NESS
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luiy's curator insight, February 22, 2014 7:58 AM

"Influence" doesn't necessarily mean what you think it does. In the age of the social-media celebrity, a glut of Twitter followers or particularly pugnacious sampling of pithy updates are often the hallmarks of an influencer. But new research suggests that influence is situational at best: as people compete for the attention of the broader online ecosystem, the relevance of your message to the existing conversation of those around you trumps any innate "power" a person may have.

 

.... According to co-author Vespignani, having millions of followers does not denote an important message. Rather, the messages with the most immediate relevance tend to have a higher probability of resonating within a certain network than others. Think of it as "survival of the fittest" for information: those tweets that capture the most attention, whether related to a major geopolitical or news event or a particular interest, are likely to persist longer. This competition sounds bad, but it's generally good for messages in general: thousands of tweets about Japan's 2011 earthquake or the ongoing conflict in Syria don't cancel each other out, but help refocus the attention of the wider Twitter audience on those issues, which in turn provides an added lift to individual messages over other off-topic ones.

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What Big Data Means For Social Science

We've known big data has had big impacts in business, and in lots of prediction tasks. I want to understand, what does big data mean for what we do for science? Specifically, I want to think about the following context:  You have a scientist who has a hypothesis that they would like to test, and I want to think about how the testing of that hypothesis might change as data gets bigger and bigger. So that's going to be the rule of the game. Scientists start with a hypothesis and they want to test it; what's going to happen?

 


Via Alessandro Cerboni, NESS, Complexity Digest, Roger D. Jones, PhD
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