e-Xploration
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Definitions That Matter (Of "Digital Humanities")

Definitions That Matter (Of "Digital Humanities") | e-Xploration | Scoop.it
In a recent post, “‘Digital Humanities’: Two Definitions,” I tried to point out an ongoing conflict in the deployment of the term “Digital Humanities.” While my goal was in part to show the practical range in definitions of DH, that was not really...

Via Rob Kitchin
luiy's insight:

I was curious about how this pattern has played out in the actual grants, so I read through several lists of the grants ODH has awarded since it was formed in 2007. I’ll admit that I was surprised by how exactly this funding conforms, almost entirely, to the narrow definition.

 

I couldn’t find an easy way to download all of the data, so here I’ve compiled a table of the ODH grants in 2010 (I’ve uploaded the complete data in anExcel spreadsheet of 2010 ODH grants). I’ve broken them down into categories that I’ve tried to make as fair as possible. There are just under $5 million in grants; of that about 1/3 goes to archives, 1/3 to tool-building, and 1/3 to workshops; in terms of the number of grants awarded the percentages are slightly different, but still go almost entirely to these three activities. There is exactly 1 grant that can reasonably be said to foreground interpretation or analysis. There are none that “study the impact of digital technology.” Based on my reading of the recent NEH records, this is a representative sample of ODH funding, and it is important to reiterate that while it by no means encompasses all of the grants NEH awarded that touched on digital topics, it does include all of the ODH grants, and therefore all of the grants formally labeled “Digital Humanities.” What is especially notable is exactly what the change in ODH mission wording would lead one to expect: there is virtually no funding for interpretation, analysis, or tool use as a primary activity. (The only topic that arguably might be framed misleadingly by my rough categorization is pedagogy, but only very subtly so: between a third and a half of the 12 workshops can be said to have pedagogy as a focus of the workshop being held–that is, they are workshops for teachers and other educators– but as Katherine Harris so rightly keeps emphasizing, this is not direct funding for pedagogical projects.)

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Intriguing Networks's curator insight, April 7, 2013 4:33 AM

everyone seems to spend a lot of time defining but does it matter or should it be fluid by the nature of the beast...

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Internet Census 2012

Internet Census 2012 | e-Xploration | Scoop.it
luiy's insight:

Abstract While playing around with the Nmap Scripting Engine (NSE) we discovered an amazing number of open embedded devices on the Internet. Many of them are based on Linux and allow login to standard BusyBox with empty or default credentials. We used these devices to build a distributed port scanner to scan all IPv4 addresses. These scans include service probes for the most common ports, ICMP ping, reverse DNS and SYN scans. We analyzed some of the data to get an estimation of the IP address usage. 

All data gathered during our research is released into the public domain for further study. 




1 Introduction 

Two years ago while spending some time with the Nmap Scripting Engine (NSE) someone mentioned that we should try the classic telnet login root:root on random IP addresses. This was meant as a joke, but was given a try. We started scanning and quickly realized that there should be several thousand unprotected devices on the Internet. 

After completing the scan of roughly one hundred thousand IP addresses, we realized the number of insecure devices must be at least one hundred thousand. Starting with one device and assuming a scan speed of ten IP addresses per second, it should find the next open device within one hour. The scan rate would be doubled if we deployed a scanner to the newly found device. After doubling the scan rate in this way about 16.5 times, all unprotected devices would be found; this would take only 16.5 hours. Additionally, with one hundred thousand devices scanning at ten probes per second we would have a distributed port scanner to port scan the entire IPv4 Internet within one hour.

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Monitor Twitter Search via Email – SoftLayer Blog

Monitor Twitter Search via Email – SoftLayer Blog | e-Xploration | Scoop.it
luiy's insight:

About three weeks ago, Hazzy stopped by my desk and asked if I’d help build a tool that uses the Twitter Search API to collect brand keywords mentions and send an email alert with those mentions in digest form every 30 minutes. The social media team had been using Twilert for these types of alerts since February 2012, but over the last few months, messages have been delayed due to issues connecting to Twitter search … It seems that the service is so popular that it hits Twitter’s limits on API calls. An email digest scheduled to be sent every thirty minutes ends up going out ten hours late, and ten hours is an eternity in social media time. We needed something a little more timely and reliable, so I got to work on a simple “Twitter Monitor” script to find all mentions of our keyword(s) on Twitter, email those results in a simple digest format, and repeat the process every 30 minutes when new mentions are found.

 

With Bear’s Python-Twitter library on GitHub, connecting to the Twitter API is a breeze. Why did we use Bear’s library in particular? Just look at his profile picture. Yeah … ’nuff said. So with that Python wrapper to the Twitter API in place, I just had to figure out how to use the tools Twitter provided to get the job done. For the most part, the process was very clear, and Twitter actually made querying the search service much easier than we expected. The Search API finds all mentions of whatever string of characters you designate, so instead of creating an elaborate Boolean search for “SoftLayer OR #SoftLayer OR @SoftLayer …” or any number of combinations of arbitrary strings, we could simply search for “SoftLayer” and have all of those results included. If you want to see only @ replies or hashtags, you can limit your search to those alone, but because “SoftLayer” isn’t a word that gets thrown around much without referencing us, we wanted to see every instance. This is the code we ended up working with for the search functionality:

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pyvideo.org - Analyzing Social Networks with Python

Social Network data is not just Twitter and Facebook - networks permeate our world - yet we often don't know what to do with them.
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A large-scale community structure analysis in Facebook

Understanding social dynamics that govern human phenomena, such as communications and social relationships is a major problem in current computational social sciences. In particular, given the unprecedented success of online social networks (OSNs), in this paper we are concerned with the analysis of aggregation patterns and social dynamics occurring among users of the largest OSN as the date: Facebook. In detail, we discuss the mesoscopic features of the community structure of this network, considering the perspective of the communities, which has not yet been studied on such a large scale. To this purpose, we acquired a sample of this network containing millions of users and their social relationships; then, we unveiled the communities representing the aggregation units among which users gather and interact; finally, we analyzed the statistical features of such a network of communities, discovering and characterizing some specific organization patterns followed by individuals interacting in online social networks, that emerge considering different sampling techniques and clustering methodologies. This study provides some clues of the tendency of individuals to establish social interactions in online social networks that eventually contribute to building a well-connected social structure, and opens space for further social studies.

 

A large-scale community structure analysis in Facebook
Emilio Ferrara

EPJ Data Science 2012, 1:9 http://dx.doi.org/10.1140/epjds9


Via Complexity Digest
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Conclusions

The aim of this work was to investigate the emergence of social dynamics, organization patterns and mesoscopic features in the community structure of a large online social network such as Facebook. This task was quite thrilling and not trivial, since a number of theoretical and computational challenges raised.

First of all, we collected real-world data directly from the online network. In fact, as recently put into evidence in literature [40], the differences between synthetic and real-world data have profound implications on results.

After we reconstructed a sample of the structure of the social graph of Facebook, we unveiled its community structure. The main findings that emerged from the mesoscopic analysis of the community structure of this network can be summarized as follows:

(i) We assessed the tendency of online social network users to constitute communities of small size, proving the presence of a decreasing number of communities of larger size. This behavior explains the tendency of users to self-organization even in absence of a coordinated effort.

(ii) We investigated the occurrence of connections among communities, finding that some kind of links, commonly referred as to weak ties, are more relevant than others because they connect communities each other, according to the Granovetter’s strength of weak ties theory[24] and in agreement with recent studies on other online social networks such as Twitter [21].

(iii) The community structure is highly clusterized and the diameter of the community structure meta-network is small (approximately around 4 and 5). These aspects indicate the presence of thesmall world phenomenon, which characterizes real-world social networks, according to sociological studies envisioned by Milgram [23] and in agreement with some heuristic evaluations recently provided by Facebook [18,19].

The achieved results open space for further studies in different directions. As far as it concerns our long-term future research directions, we plan to investigate, amongst others, the following issues:

(i) Devising a model to identify the most representative users inside each given community. This would leave space for further interesting applications, such as the maximization of advertising on online social networks, the analysis of communication dynamics, spread of influence and information and so on.

(ii) Exploiting geographical data regarding the physical location of users of Facebook, to study the effect of strong and weak ties in the society [24]. In fact, is it known that a relevant additional source of information is represented by the geographical distribution of individuals [68-70]. For example, we suppose that strong ties could reflect relations characterized by physical closeness, while weak ties could be more appropriate to represent connections among physically distant individuals.

(iii) Concluding, we devised a strategy to estimate the strength of ties between social network users [71] and we want to study its application to online social networks on a large scale. In the case of social ties, this is equivalent to estimate the friendship degree between a pair of users by considering their interactions and their attitude to exchange information.

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Web analytics In Real Time

Web analytics In Real Time | e-Xploration | Scoop.it

Mankind loves making maps, and the world wide web, densely interconnected and phenomenally complex, always makes for a nice visual.

Typically these take the form of neon blobs floating against black backgrounds, like frames captured from old Winamp plug-ins, and while they’re always nice to look at, they don’t always do much in the way of helping us understand the massive global network we traverse every day. This latest effort, however, is a little different. Called simply Map of the Internet, it’s as informative as it is beautiful.


The map, which takes the form of a free app for Android and iOS, features 22,961 of the Internet’s biggest nodes--not individual websites, but the ISPs, universities, and other places that host them--joined by some 50,000 discrete connections. The app gives you two ways of surveying it all: geographically, on a globe, or by size, which rearranges the nodes into a loose column of points. Both views are interactive; instead of showing the Internet as a static neon blob, the app lets you explore the neon blob in the round, with all the familiar multitouch gestures. It may not look like the Google Maps app, but it instantly feels like it, which makes exploring the underbelly of the web all the easier...


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Chaos and Butterfly Effect - Sixty Symbols

The butterfly effect is associated with the unpredictable world of chaos... Two of our physicists have a chat about it. They are Laurence Eaves and Mark From...

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Competition among memes in a world with limited attention : Scientific Reports : Nature Publishing Group

Competition among memes in a world with limited attention : Scientific Reports : Nature Publishing Group | e-Xploration | 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.

luiy's insight:

MODEL DESCRIPTION.

 

Our basic model assumes a frozen network of agents. An agent maintains a time-ordered list ofposts, each about a specific meme. Multiple posts may be about the same meme. Users pay attention to these memes only. Asynchronously and with uniform probability, each agent can generate a post about a new meme or forward some of the posts from the list, transmitting the corresponding memes to neighboring agents. Neighbors in turn pay attention to a newly received meme by placing it at the top of their lists. To account for the empirical observation that past behavior affects what memes the user will spread in the future, we include a memory mechanism that allows agents to develop endogenous interests and focus. Finally, we model limited attentionby allowing posts to survive in an agent's list or memory only for a finite amount of time. When a post is forgotten, its associated meme become less represented. A meme is forgotten when the last post carrying that meme disappears from the user's list or memory. Note that list and memory work like first-in-first-out rather than priority queues, as proposed in models of bursty human activity34. In the context of single-agent behavior, our memory mechanism is reminiscent of the classic Yule-Simon model∼\cite{yule-simon43, Cattuto3001200744}.

 

The retweet model we propose is illustrated in Fig. 5. Agents interact on a directed social network of friends/followers. Each user node is equipped with a screen where received memes are recorded, and a memory with records of posted memes. An edge from a friend to a follower indicates that the friend's memes can be read on the follower's screen (#x and #y in Fig. 5(a)appear on the screen in Fig. 5(b)). At each step, an agent is selected randomly to post memes to neighbors. The agent may post about a new meme with probability pn (#z in Fig. 5(b)). The posted meme immediately appears at the top of the memory. Otherwise, the agent reads posts about existing memes from the screen. Each post may attract the user's attention with probability pr (the user pays attention to #x, #y in Fig. 5(c)). Then the agent either retweets the post (#x in Fig. 5(c)) with probability 1 − pm, or tweets about a meme chosen from memory (#v triggered by #y in Fig. 5(c)) with probability pm. Any post in memory has equal opportunities to be selected, therefore memes that appear more frequently in memory are more likely to be propagated (the memory has two posts about #v in Fig. 5(d)). To model limited user attention, both screen and memory have a finite capacity, which is the time in which a post remains in an agent's screen or memory. For all agents, posts are removed after one time unit, which simulates a unit of real time, corresponding toNu steps where Nu is the number of agents. If people use the system once weekly on average, the time unit corresponds to a week.

 

 

DISCUSSION.

 

The present findings demonstrate that the combination of social network structure and competition for finite user attention is a sufficient condition for the emergence of broad diversity in meme popularity, lifetime, and user activity. This is a remarkable result: one can account for the often-reported long-tailed distributions of topic popularity and lifetime7, 12, 14, 29 without having to assume exogenous factors such as intrinsic meme appeal, user influence, or external events. The only source of heterogeneity in our model is the social network; users differ in their audience size but not in the quality of their messages.

 

Our model is inspired by the long tradition that represents information spreading as an epidemic process, where infection is passed along the edges of the underlying social network35, 36, 37, 7, 28,12.

In the context of social media, several authors explored the temporal evolution of popularity. Wu and Huberman8 studied the decay in news popularity. They showed that temporal patterns of collective attention are well described by a multiplicative process with a single novelty factor. While the decay in popularity is attributed to competition for attention, the underlying mechanism is not modeled explicitly. Crane and Sornette10 introduced a model to describe the exogenous and endogenous bursts of attention toward a video, by combining an epidemic spreading process with a forgetting mechanism. Hogg and Lerman38 proposed a stochastic model to predict the popularity of a news story via the intrinsic interest of the story and the rates at which users find it directly and through friends. These models describe the popularity of a single piece of information, and are therefore unsuitable to capture the competition for our collective attention among multiple simultaneous information epidemics. Although recent epidemiological models have started considering the simultaneous spread of competing strains39, 40, our framework is the first attempt to deal with a virtually unbounded number of new “epidemics” that are continuously injected into the system. A closer analogy to our approach is perhaps provided by neutral models of ecosystems, where individuals (posts) belonging to different species (memes) produce offspring in an environment (our collective attention) that can sustain only a limited number of individuals. At every generation, individuals belonging to new species enter the ecosystem while as many individuals die as needed to maintain the sustainability threshold41.

 

Since Simon’s seminal paper4, the economy of attention has been an enormously popular notion, yet it has always been assumed implicitly and never put to the test. Our model provides a first attempt to focus explicitly on mechanisms of competition, and to evaluate the quantitative effects of making attention more scarce or abundant.

 

Our results do not constitute a proof that exogenous features, like intrinsic values of memes, play no role in determining their popularity. However we have shown that at the statistical level it is not necessary to invoke external explanations for the observed global dynamics of memes. This appears as an arresting conclusion that makes information epidemics quite different from the basic modeling and conceptual framework of biological epidemics. While the intrinsic features of viruses and their adaptation to hosts are extremely relevant in determining the winning strains, in the information world the limited time and attention of human behavior are sufficient to generate a complex information landscape and define a wide range of different meme spreading patterns. This calls for a major revision of many concepts commonly used in the modeling and characterization of meme diffusion and opens the path to different frameworks for the analysis of competition among ideas and strategies for the optimization/suppression of their spread.

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This Is What The Internet Looks Like

This Is What The Internet Looks Like | e-Xploration | Scoop.it
Peer 1 Hosting has been trying to explain what the Internet looks like since 2011, when they created an infographic
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Peer 1 Hosting has been trying to explain what the Internet looks like since 2011, when they created an infographic map of the Internet showing networks and routing connections across the world. Now they've visualized the web in a zoomable Map of the Internet app for iPhone andAndroid that lets you explore connectivity in a more hands-on way.

 

Using data from CAIDA, The Cooperative Association for Internet Data Analysis, the app shows 22,961 autonomous system nodes and the 50,519 connection that link them, both from a global view and a network view. Exploring it is a little like being lost in space, surrounded by floating lights and colors.

 

You can search for particular companies or domains and perform traceroutes to see how data moves between them, or you can also watch the Internet evolve over time. A timeline at the bottom pinpoints important years in the history of the web, like the launch of Wikipedia or last year's SOPA blackout, and lets you explore how connectivity has increased over the years. Based on current data, they even predict what the Internet landscape will look like in 2020.

 

In the blog post announcing the app release, the company says they think of the map as "an educational tool that represents the Internet’s evolution from 1994 to present day." Unless you already know a lot about networks and autonomous systems, it might more disorienting than educational, but at least it's fun to play with.

 

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To Improve Conversations, Facebook Will Launch A Reply Feature And Most Active Threads On Pages And Popular Profiles

To Improve Conversations, Facebook Will Launch A Reply Feature And Most Active Threads On Pages And Popular Profiles | e-Xploration | Scoop.it
Facebook is preparing to roll out a new feature on Pages and popular Profiles that will help increase interactions with fans and readers: Replies.
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Facebook is preparing to roll out a new feature on Pages and popular Profiles that will help increase interactions with fans and readers: Replies. Up to now, visitors could comment on a post but others, including the Page owners themselves, would not be able to respond directly to them in cases of multiple people commenting on a post. Facebook has been running tests of the new feature since November last year; now a source tells us it will be rolling out the feature more formally as an opt-in on Monday, March 25, before turning it on for everyone in July.

 

Update: Facebook has now confirmed this story and rollout plans. “We think this update will allow for easier management of conversations around posts, which is a better experience for people interacting with Pages and public figure profiles,” a spokesperson said. (original story continues below)


To the right is a sample screen shot of how it looks from a page that has been testing the comments already. (Update: this is replacing the grainy picture used previously.)

 

Another feature that will be launched at the same time is active-thread sifting, which also had been in beta testing. Here, the most active conversations will be ordered at the top using an algorithm to appear higher in the posts.

 

Replies and the algorithmic sorting won’t work everywhere. They are being rolled out only to Page posts and Profiles with more than 10,000 followers, not personal accounts. Also, they will not work on mobile, although the intention is to make Replies part of the Graph API and mobile in the future.

 

Replies are already a part of Facebook’s commenting plug-in, which runs on third-party sites (TechCrunch used to use it; it doesn’t anymore). But this is the first time Replies will be appearing across Facebook itself.

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Cloud and Big Data, Together: A Huge Springboard to Innovation - Forbes

Cloud and Big Data, Together: A Huge Springboard to Innovation - Forbes | e-Xploration | Scoop.it
"Big data is the new cloud computing." This sentiment was recently expressed in an interview with Motley Fool analyst Tim Byers, who analyzed the zeitgeist coming out of the South-by-Southwest (SXSW) conference and observed that cloud computing and...

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Buying Our Way into Bondage: The Risks of Adaptive Learning Services - David Wiley

The Perfect Storm Much of the education technology world - and many of the foundations and venture firms that provide the funding for it - are obsessed with adaptive learning. The Gates Foundation'...

Via Ana Cristina Pratas, Pierre Levy
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Ana Cristina Pratas's curator insight, March 22, 2013 12:08 AM

Adaptive learning services are a perfect response to the business model challenges presented by OER to publishers. While the broad availability of free content (e.g., CNN.com) and OER have trained internet users to expect content to be free, many people are still willing to pay for services. Adaptive learning systems exploit this willingness by deeply intermingling content and services so that you cannot access one with using the other. Naturally, because an adaptive learning service is comprised of content plus adaptive services, it will be more expensive than static content used to be. And because it is a service, you cannot simply purchase it like you used to buy a textbook (particularly useful for publishers given the Court’s recent decision upholding the first sale doctrine with regard to textbooks). An adaptive learning service is something you subscribe to, like Netflix. And just like with Netflix, the day you stop paying for the service is the day you lose access to the service.

Helena Capela's curator insight, March 22, 2013 7:08 AM

interesting article on the implications of openness, OER, the end of textbooks and the end of ownership if the trend is adaptive learning services

Brad Ovenell-Carter's curator insight, March 22, 2013 2:00 PM

Ana's comments are worth noting. I wonder if, as a way out of the problem, we look at the state somehow take over the delivery/ownership model. Public edcuation is done, as it is. (See my ost http://www.ovenell-carter.com/education-aint-broke-so-dont-fix-it/) It's neither sustainable nor scalable. I believe we need a whole new structure; the current new option, as described in this article, is problematic. BUt some variation might work.

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e-littérature - Mise à disposition des articles de recherche de Jean-Pierre Balpe

e-littérature - Mise à disposition des articles de recherche de Jean-Pierre Balpe | e-Xploration | Scoop.it
blog sur la e-littérature contient des articles sur les installations, la génération automatique de texte et la littérature interactive.

 

Jean-Pierre Balpe est directeur du département hypermédias et du laboratoire Paragraphe de l'Université de Paris 8. Il est également secrétaire général de la revue Action poétique. Chercheur, théoricien de la littérature informatique, auteur de divers ouvrages scientifiques et techniques (dernier ouvrage paru: Contextes de l'art numérique, Hermès, 2000), écrivain, après avoir très longtemps écrit des poèmes et nouvelles publiés dans diverses revues, il s'intéresse dès 1975 aux possibilités que l'informatique offre à l'écriture littéraire. En 1981 il est un des cofondateurs de l'ALAMO (Atelier de littérature assistée par la mathématique et les ordinateurs) et, à ce titre, conseiller auprès de la BPI (Bibliothèque publique d'information) pour les expositions "Les Immatériaux" et "Mémoires du futur". En 1985 il conçoit pour l'INA (Institut national de l'audiovisuel) et France Télécom le premier scénario de télévision interactive, diffusé alors par Canal +.

 

Depuis 1989, il réalise des logiciels d'écriture principalement utilisés lors d'expositions ou de manifestations publiques, notamment Un roman inachevé pour le stand du ministère de la Culture au MILIA (Marché international du livre illustré et des nouveaux médias) à Cannes et au MIM (Marché international du multimédia de Montréal) en 1995, Romans (Roman) pour l'exposition "Artifices" de novembre 1996 ou sous forme de spectacles comme Trois mythologies et un poète aveugle, première oeuvre générative collaborant avec un générateur musical. Il a actuellement en chantier un opéra numérique, Barbe-Bleue, résultat de la collaboration de trois générateurs: générateur de texte (le sien), générateur de musique (Alexandre Raskatov) et générateur de scénographie (Michel Jaffrennou). Il est également l'auteur de Trajectoires, un roman génératif en ligne.


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Parsing the humanities | University Affairs

Parsing the humanities | University Affairs | e-Xploration | Scoop.it
Everything you wanted to know about digital humanities.

Via Pierre Levy
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Pierre Levy's curator insight, March 15, 2013 1:45 PM

A canadian point of view...

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Big Data and a Renewed Debate Over Privacy

Big Data and a Renewed Debate Over Privacy | e-Xploration | Scoop.it
The dawn of mainframe computers offered huge technological benefits, but also challenged notions of privacy. Now Big Data is bringing similar expectations and concerns.

Via Pierre Levy, Rui Guimarães Lima
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Pierre Levy's curator insight, March 24, 2013 5:43 PM

The privacy backlash...

Intriguing Networks's curator insight, March 25, 2013 7:22 AM

Mainframe and Big Data Privacy the debate continues but is it any dfferent?

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Student Attention, Engagement and Participation in a Twitter-friendly Classroom

Guided by a participatory action research methodology, this paper outlines an approach to integrating the social media Twitter platform within a tertiary education course, based on a social, constructivist pedagogy. It explores the perceptions of students on the benefits of using this technology for enhancing attentiveness, engagement and participation in the classroom. Previous studies have shown that greater participation and communication can stimulate student learning and lead to better academic performance, increased motivation, and an appreciation of different points of views. The untested hypothesis is that social media tools like Twitter can foster this type of communication. Students posted their responses during classroom activities via Twitter

and then were surveyed on their perceived benefits associated with using the social media platform. The preliminary findings of the qualitative study suggest that, while not without its challenges, social media tools like Twitter have the potential to be used effectively for education-based activities in the classroom to improve communication and engagement both amongst the students and with the instructor.

 

PDF Copy: http://dro.deakin.edu.au/eserv/DU:30049108/ally-studentattention-2012.pdf

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Share Your Google Analytics Data As An Infographic

Share Your Google Analytics Data As An Infographic | e-Xploration | Scoop.it

Wouldn’t it be great to get weekly website performance updates as a simple, easy-to-read graphic?

Now you can go beyond the Google Analytics dashboard with a new creative  – and free – tool by Visual.ly. The New Google Analytics Report automatically delivers an infographic depicting your favorite metrics right to your desktop. See the infographic at the article link for a sample of a full infographic that is generated...


Via Lauren Moss
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Didde Glad's curator insight, March 24, 2013 5:52 PM

Præsentér ledelsesinformation i GRATIS designet dashboard med gnaske få klik 

 

 

 

 

ParadigmGallery's comment, March 25, 2013 11:48 AM
did it, interesting, not so sure the artsy, soft approach to the analytics report is as visually satisfying as the bright, primary colors of google.....
AlGonzalezinfo's curator insight, April 9, 2013 10:03 PM

Awesome scoop, thanks Robin!

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The Complexity Leadership Theory (CLT)

The Complexity Leadership Theory (CLT) | e-Xploration | Scoop.it
The Complexity Leadership Theory (CLT) starts with the notion of Complex Adaptive Systems (CAS), which are a basic unit of analysis in complexity science.

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Piratical Practices - a theory/practice project - remix + appropriation + [de]collage + intellectual property...

Piratical Practices - a theory/practice project - remix + appropriation + [de]collage + intellectual property... | e-Xploration | Scoop.it

Piratical Practices is a theory/practice project exploring the aestheticonceptechniques && intersections of remix + appropriation + [de]collage + intellectual property + sampling + plunderphonics + detournement + plagiarism + versioning + sharing + [etc] w/ a focus on our technological times ✄ ☠ ✍


Via Jacques Urbanska
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European Cybercrime Center (EC3)

European Cybercrime Center (EC3) | e-Xploration | Scoop.it

With increasing cybercrime targeting citizens, businesses and governments EC3 came operational on 11 January 2013 be the focal point in the EU’s fight against cybercrime.

The European Union is a key target because of Internet-based economies and payment systems and its advanced Internet infrastructure.

EC3 will support Member States and the European Union’s institutions in building operational and analytical capacity for investigations and cooperation with international partners.


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Visualize the whole Internet with an app

Peer 1 Hosting has a new app that allows you to see the interconnecting servers that make up the Internet around the world.
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CIA Chief Tech Officer: Big Data Is The Future And We Own It

CIA Chief Tech Officer: Big Data Is The Future And We Own It | e-Xploration | Scoop.it
Soon "able to compute on all human generated information."
luiy's insight:

"You're already a walking sensor platform," Hunt said, referring to all of the information captured by smartphones. "You are aware of the fact that somebody can know where you are at all times because you carry a mobile device, even if that mobile device is turned off. You know this, I hope? Yes? Well, you should."

 

In fact Hunt noted that based on the sensors in a smartphone, someone can be identified (with 100 percent accuracy) by the way they walk — implying that someone could be identified even when carrying someone else's phone.

The challenge for the CIA is to find the relevance is the ocean of information when something happens. The first step is for "data scientists" to save and analyze all digital breadcrumbs — even the ones people don't know they are creating (i.e. "More is always better").

 

"Since you can't connect dots you don't have, it drives us into a mode of, we fundamentally try to collect everything and hang on to it forever," Hunt said. "It is really very nearly within our grasp to be able to compute on all human generated information." 

 

He ends with comments about how the "inanimate is becoming sentient," how cognitive machines (e.g. Watson) are going to "explode upon us," and how technology is moving faster than governments, legal systems, and even individuals can keep up.



Read more: http://www.businessinsider.com/cia-presentation-on-big-data-2013-3?op=1#ixzz2OMbJzqLV

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Social data is not like most #bigdata. by @ValdisKrebs | #sna #methods

Social data is not like most #bigdata. by @ValdisKrebs | #sna #methods | e-Xploration | Scoop.it
luiy's insight:

When investigating social/relational data, it is usually not the forest that is useful, but the clusters of various trees, and their relationships, inside the ecosystem. We not only want to "see the forest for the trees", but also see the patterns/clusters of trees in the forest! 

Unless the bar has been set too low, for what a link is, most collections of big data on social relationships contain hundreds, if not thousands, of components/subsets.  Patterns reveal much within interlinked data. As we zoom in, we can begin to answer some useful questions :

 

- Who is here?  

- How are they clustered? 

- How are they connected? 

- Who are the key connectors?  

- Who is in the thick of things?

 

Below are various subsets of the above ecosystem -- we put an MRI to our big data pile.  These network maps show various slices of the whole, and how they are connected. We now see patterns worth investigating.

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Emergence in stigmergic and complex adaptive systems: A formal discrete event systems perspective

Emergence in stigmergic and complex adaptive systems: A formal discrete event systems perspective | e-Xploration | Scoop.it
Some extracts from Saurabh Mittal’s paper. A natural system is not a monolithic system but a heterogeneous system made up of disparity and dissimilarity, devoid of any larger goal.

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Visual.ly’s new Google Analytics tool sends you weekly Web metric reports as infographics

Visual.ly’s new Google Analytics tool sends you weekly Web metric reports as infographics | e-Xploration | Scoop.it

"We're big fans of Visual.ly here at TNW, ever since it launched as the home of data visualization and infographics way back in July 2011.

The platform has evolved somewhat since then, launching Visual.ly Create for users to create their own infographics with ease, before going on to roll out a complete redesign with social features last July. And then in October, Visually unveiled a new marketplace to help put its community of infographic designers to work

So, when we got wind of Visual.ly’s latest launch, naturally we were all ears (well, eyes). The Israeli startup has launched a new visual reporting tool designed to bring Google Analytics to your email inbox courtesy of a weekly infographic....


Via siobhan-o-flynn, blogbrevity
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