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Look Out Klout, These Twitter Influencer Maps Are Amazing

Look Out Klout, These Twitter Influencer Maps Are Amazing | Social Network Analysis | Scoop.it
What if instead of a score, you could visualize the impact a person, business or topic has in a social network?
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Open Data Tools: Turning Data into ‘Actionable Intelligence’

Open Data Tools: Turning Data into ‘Actionable Intelligence’ | Social Network Analysis | Scoop.it
My previous two articles were on open access and open data. They conveyed major changes that are underway around the globe in the methods by which scientific an

Via Ivan Begtin
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luiy's curator insight, July 16, 2013 6:12 AM

The truth is, many scientists are routinely employed in hacking their own programs to link measuring equipment, data analysis, and visualization together and my best guess is that they would benefit from more end-to-end integrative open source software systems development.

 

While by no means exhaustive, I compiled a list linking to 349 subject specific tools and 123 general tools that are useful for all of this newly available open data. Certainly, some if not all of the tools in this list might have its quality rated according to the eight aforementioned standards.

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New algorithm solves a major problem with cloud encryption

New algorithm solves a major problem with cloud encryption | Social Network Analysis | Scoop.it
Homomorphic encryption is one of the most exciting new research topics in cryptography, which promises to make cloud computing perfectly secure. With it, a Web user would send encrypted data to a s...

Via Pierre Levy
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THIS is social: Every service you need to know right now in one graphic

THIS is social: Every service you need to know right now in one graphic | Social Network Analysis | Scoop.it
Change is the only constant in the online frontier of social media, which is documented by the latest iteration of Brian Solis' Conversation Prism.
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Rescooped by Jay Ratcliff from Anthropology, communication & technology
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Twitter Makes Crowds Less Predictable: Scientific American

Twitter Makes Crowds Less Predictable: Scientific American | Social Network Analysis | Scoop.it
The protests in Turkey demonstrate the social physics of highly connected crowds

 

Twitter became the principal communication tool for the protesters; a diverse and previously politically inactive people self-mobilized; and the uprising caught most observers by surprise. These three features may be interrelated. There is an emerging understanding of the relationship between connectedness and collective decisions. As one would expect, when people are better connected, they tend to unite around popular decisions. But research also suggests that social connection — fostered by Twitter, say — also makes crowds fundamentally less predictable. With social media connecting people to an unprecedented degree, it is possible that the sudden emergence of unexpected collective action will be a defining feature of this era.


Via John Postill, Andrea Naranjo
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John Postill's curator insight, June 20, 2013 3:08 AM

Liberationtech ‏@Liberationtech 3h

#Turkey Shows Twitter Makes Crowds Less Predictable http://www.scientificamerican.com/article.cfm?id=twitter-makes-crowds-less-predictable … by @ozgunatasoy HT @OlgaWerby

 
Rescooped by Jay Ratcliff from BIG data, Data Mining, Predictive Modeling, Visualization
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Land Registry goes big on open data | Open Data Institute

Good to see @LandRegGov opening up its historical price paid data today http://t.co/sLNXksXBKN - more power to #opendata

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Use These Secret NSA Google Search Tips to Become Your Own Spy Agency | Wired.com

Use These Secret NSA Google Search Tips to Become Your Own Spy Agency | Wired.com | Social Network Analysis | Scoop.it
Want to know how to "'hack" Google like the pros? The NSA has released a book it produced for its workers on how to find intelligence on the web.

Via Pierre Levy
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luiy's curator insight, July 12, 2013 2:09 PM

The 643-page tome, called Untangling the Web: A Guide to Internet Research (.pdf), was just released by the NSA following a FOIA request filed in April by MuckRock, a site that charges fees to process public records for activists and others.

 

The book was published by the Center for Digital Content of the National Security Agency, and is filled with advice for using search engines, the Internet Archive and other online tools. But the most interesting is the chapter titled “Google Hacking.”

 

Say you’re a cyberspy for the NSA and you want sensitive inside information on companies in South Africa. What do you do?

Search for confidential Excel spreadsheets the company inadvertently posted online by typing “filetype:xls site:za confidential” into Google, the book notes.

 

Want to find spreadsheets full of passwords in Russia? Type “filetype:xls site:ru login.” Even on websites written in non-English languages the terms “login,” “userid,” and “password” are generally written in English, the authors helpfully point out.

 

Misconfigured web servers “that list the contents of directories not intended to be on the web often offer a rich load of information to Google hackers,” the authors write, then offer a command to exploit these vulnerabilities — intitle: “index of” site:kr password.

 

“Nothing I am going to describe to you is illegal, nor does it in any way involve accessing unauthorized data,” the authors assert in their book. Instead it “involves using publicly available search engines to access publicly available information that almost certainly was not intended for public distribution.” You know, sort of like the “hacking” for which Andrew “weev” Aurenheimer was recently sentenced to 3.5 years in prison for obtaining publicly accessible information from AT&T’s website.

 

Stealing intelligence on the internet that others don’t want you to have might not be illegal, but it does come with other risks, the authors note: “It is critical that you handle all Microsoft file types on the internet with extreme care. Never open a Microsoft file type on the internet. Instead, use one of the techniques described here,” they write in a footnote. The word “here” is hyperlinked, but since the document is a PDF the link is inaccessible. No word about the dangers that Adobe PDFs pose. But the version of the manual the NSA released was last updated in 2007, so let’s hope later versions cover it.

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Open Data Implementation in Six Steps

Open Data Implementation in Six Steps | Social Network Analysis | Scoop.it
Simplify your implementation efforts by focusing on phases. Read examples of others’ success.
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PLOS ONE: Scaling-Laws of Human Broadcast Communication Enable Distinction between Human, Corporate and Robot Twitter Users

PLOS ONE: Scaling-Laws of Human Broadcast Communication Enable Distinction between Human, Corporate and Robot Twitter Users | Social Network Analysis | Scoop.it

Human behaviour is highly individual by nature, yet statistical structures are emerging which seem to govern the actions of human beings collectively. Here we search for universal statistical laws dictating the timing of human actions in communication decisions. We focus on the distribution of the time interval between messages in human broadcast communication, as documented in Twitter, and study a collection of over 160,000 tweets for three user categories: personal (controlled by one person), managed (typically PR agency controlled) and bot-controlled (automated system). To test our hypothesis, we investigate whether it is possible to differentiate between user types based on tweet timing behaviour, independently of the content in messages. For this purpose, we developed a system to process a large amount of tweets for reality mining and implemented two simple probabilistic inference algorithms: 1. a naive Bayes classifier, which distinguishes between two and three account categories with classification performance of 84.6% and 75.8%, respectively and 2. a prediction algorithm to estimate the time of a user's next tweet with an . Our results show that we can reliably distinguish between the three user categories as well as predict the distribution of a user's inter-message time with reasonable accuracy. More importantly, we identify a characteristic power-law decrease in the tail of inter-message time distribution by human users which is different from that obtained for managed and automated accounts. This result is evidence of a universal law that permeates the timing of human decisions in broadcast communication and extends the findings of several previous studies of peer-to-peer communication.


Via Andrea Naranjo
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luiy's curator insight, July 4, 2013 7:47 AM

We are investigating here to what extent these computational neuroscience approaches can be applied to analyse human communication decisions on the online social network Twitter, specifically to understand the timing of tweeting. We follow a very simple, easily interpretable approach using non-parametric Bayesian statistics to analyse and then predict the nature of the tweeter, i.e., is the tweeter a genuine individual or somebody or something else.

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Game Theory is No Longer Just for Economists. Now Engineers and Computer Scientists Like MIT’s Asuman Ozdaglar, Constantinos Daskalakis, Silvio Micali, Munther Dahleh, and Mardavij Roozbehani are U...

Game Theory is No Longer Just for Economists. Now Engineers and Computer Scientists Like MIT’s Asuman Ozdaglar, Constantinos Daskalakis, Silvio Micali, Munther Dahleh, and Mardavij Roozbehani are U... | Social Network Analysis | Scoop.it
Economists have long used game theory to make sense of the world. Now engineers and computer scientists are using it to rethink their work.

Via Dr. Susan Bainbridge
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DG2's curator insight, September 3, 2013 7:40 AM

Lots of sinergies here: ML/CS tools can be leveraged to obtain approximate solutions to hard game theoretical problems (like mechanism design), while at the same time game theoretical concepts inspire better, more realistic ML algorithms.