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Transition from the crisis 3,The Future of Internet: The Weave

Transition from the crisis 3,The Future of Internet: The Weave | e-Xploration | Scoop.it
EU Commissioner Neelie Kroes wrote on December 22: “We must invest in the growth sectors of the future now, to fight the crises. The Internet Sector in Europe grows with 12%/year and has the ...

Via Xaos
luiy's insight:

Living systems according to Parent (1996) are by definition “open self-organizing systems that have the special characteristics of life and interact with their environment. This takes place by means of information and material-energy exchanges. Living systems can be as simple as a single cell or as complex as a supranational organization such as the European Union. Regardless of their complexity, they each depend upon the same essential twenty subsystems (or processes) in order to survive and to continue the propagation of their species or types beyond a single generation”.[4]

Miller said that systems exist at 8 “nested” hierarchical levels: cell, organ, organism, group, organization, community, society, and supranational system. In more detail:


{{The eight levels of living systems are: cells: a basic building block of life organs: the principle components are cells, organized in simple, multi-cellular systems. organisms: there are three kinds of organisms: fungi, plants and animals. Each has distinctive cells, tissues and body plans and carries out life processes differently. groups: these contain two or more organisms and their relationships. organizations: these involve one of more groups with their own control systems for doing work. communities: they include both individual persons and groups, as well as groups which are formed and are responsible for governing or providing services to them. societies: these are loose associations of communities, with systematic relationships between and among them. supranational systems: organizations of societies with a supraordinate system of influence and control}}

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Xaos's curator insight, December 28, 2012 10:26 AM

Problem however is that not many people have a clue what Internet is or if they do   think about different things, like the World Wide Web of Apps & Cloud services. And they have a wide variety of views how “Internet” should be governed. Recently at the ITU world conference on international telecommunications (WCIT-12) in Dubai these different views came to a conflict where a number of member countries refused to sign the treaty. On the one side nation states expressed their sovereign right to regulate ( and if necessary block) internal and external Internet traffic; and on the other side countries who express the view that the Internet is by  design is a transnational structure with a “multi-stakeholder” organisation to run it and further develop it. I subscribe to this latter view and will explain in this blog why and how this can and will be done.

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antropologo.net, dataviz, collective intelligence, algorithms, social learning, social change, digital humanities
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Oycib ::: Collective Intelligence. "Kaan". Network Visualisation.

Oycib ::: Collective Intelligence. "Kaan". Network Visualisation. | e-Xploration | Scoop.it
luiy's insight:

Beginning with the origins, Oycib means in Mayan language "the place of honey". In this projet, Oycib is an e-Research infrastructure for the Collective Intelligence Analysis.

 

With Oycib infrastructure we propose an analysis model, based in the digital practices and collaboration profiles for the development of Social Learning and the Context Awareness in the Collective Intelligence process.

 

The infrastructure design and the profiles proposed here, are based on historical studies about social organization glyphs in Mayan culture made by Montgomery (2002) and Calvin (2012).

 

Initially we worked with four collaboration profiles: the "Itzaat", the "Pitziil", the "Ayuxul" and the "Sajal" (profiles), but we can find others depending of the organization context. Thus, it's important to mention that each profile is found based on the e-Xploración model and they are the qualitative and quantitative interpretation of the collaborative practices. In this way, we propose methods based on Social Network Analysis for the learning and knowledge management.

 

Thus, the network in Oycib is called "Kaan" (sky or network in Mayan Lenguage). In the "Kaan" we present the visualization of the subjects and objects, such as persons, forums, blogs, files, groups and all the interactions among them. Additionally, each profile and their interactions is presented.

 

... you can interact with "Kaan" here.

 

http://viz.oycib.org/net_all_3/network/index.html

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The Socialist Origins of #BigData | #Cybersyn #Cybernetics

The Socialist Origins of #BigData | #Cybersyn #Cybernetics | e-Xploration | Scoop.it
Evgeny Morozov on how the ideas behind Project Cybersyn, a futuristic experiment in cybernetics from nineteen-seventies Chile, still shapes technology.
luiy's insight:

The consultant, Stafford Beer, had been brought in by Chile’s top planners to help guide the country down what Salvador Allende, its democratically elected Marxist leader, was calling “the Chilean road to socialism.” Beer was a leading theorist of cybernetics—a discipline born of midcentury efforts to understand the role of communication in controlling social, biological, and technical systems. Chile’s government had a lot to control: Allende, who took office in November of 1970, had swiftly nationalized the country’s key industries, and he promised “worker participation” in the planning process. Beer’s mission was to deliver a hypermodern information system that would make this possible, and so bring socialism into the computer age. The system he devised had a gleaming, sci-fi name: Project Cybersyn.

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Machine Learning #WorkFlow | #datascience #bigdata

Machine Learning #WorkFlow | #datascience #bigdata | e-Xploration | Scoop.it
So far, I am planning to write a serie of posts explaining a basic Machine Learning work-flow (mostly supervised). In this post, my target is to propose the bird-eye view, as I'll dwell into details at the latter posts explaining each of the components in detail. I decide to write this serie due to two reasons; the first reason is self-education -to get all my bits and pieces together after a period of theoretical research and industrial practice- the second is to present a naive guide to beginn

Via ukituki
luiy's insight:

Each box has a color tone from YELLOW to RED. The yellower the box, the more this component relies on Statistics knowledge base. As the box turns into red[gets darker], the component depends more heavily on Machine Learning knowledge base. By saying this, I also imply that, without good statistical understanding, we are not able to construct a convenient machine learning pipeline. As a footnote, this schema is changed by post-modernism of Representation Learning algorithms and I'll touch this at the latter posts.

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Michael Hansmeyer: Building unimaginable shapes | #algorithms #design

luiy's insight:

Inspired by cell division, Michael Hansmeyer writes algorithms that design outrageously fascinating shapes and forms with millions of facets. No person could draft them by hand, but they're buildable -- and they could revolutionize the way we think of architectural form.
Michael Hansmeyer is an architect and programmer who explores the use of algorithms and computation to generate architectural form. Full bio: http://www.ted.com/speakers/michael_h...

 

Why you should listen

Classical architecture is defined by "orders" -- ways to connect a column to a building, to articulate the joining of materials and structural forces. Colloquially, these orders are based on elemental forms: the tree trunk, the plank, the scroll, the leaf. Michael Hansmeyer is adding a new elemental form: the subdivision algorithm. He turns his math and programming skills to making ornate, organic, hyperdetailed columns generated from lines of code and then comped up in cross-sections of cardboard, almost as if they're being 3D printed.

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Le design de la visibilité | by @Karmacoma #socialmedia #identity

Le design de la visibilité | by @Karmacoma #socialmedia #identity | e-Xploration | Scoop.it
renvoie en effet à un ensemble de pratiques hétérogènes : la participation aux débats publics, l’exposition de soi dans des récits intimes, le développement de pratiques amateurs, les bricolages (remix, sample, collage) de produits culturels standardisés, la recherche de signes de distinction, l’affirmation de choix de vie autonome, la quête de réputation, etc.
luiy's insight:

Le processus de subjectivation : l’extériorisation de soi

La première dynamique est celle de l’extériorisation de l’identité des personnes dans des signes, formulation qui recoupe, au moins partiellement, ce qui est souvent qualifié de processus de subjectivation[8]  La notion de subjectivation fait l’objet d’acceptions... [8] . Les interfaces du web 2.0 présentent toutes une entrée individuelle, une fiche de signalement, qui constitue le point de départ de toute navigation. Celle-ci enregistre certaines caractéristiques stables et durables des personnes, mais aussi et surtout des signes d’identité beaucoup plus diffus, mouvants et multiples que les participants déposent dans leurs goûts, leurs amis, leurs activités ou leurs œuvres. Ce que l’on qualifie habituellement de dynamique « expressiviste »[9]  ALLARD et VANDENBERGHE, 2003. [9] renvoie en effet à un ensemble de pratiques hétérogènes : la participation aux débats publics, l’exposition de soi dans des récits intimes, le développement de pratiques amateurs, les bricolages (remix, sample, collage) de produits culturels standardisés, la recherche de signes de distinction, l’affirmation de choix de vie autonome, la quête de réputation, etc.

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Introducing the Living With #Data series | #personalData #algorithms

Introducing the Living With #Data series | #personalData #algorithms | e-Xploration | Scoop.it
A field guide to the data and algorithms that shape our world
luiy's insight:

Literacy before legibility

 

Ads may seem innocuous, and many of us have learned to ignore them. But these ads might be some of the clearest signals we have about where our data flows and how it could be used in other contexts.

 

Each click is an input that goes in one end of the algorithmic black box, and the rest of our online experience comes out the other. Data is making our behaviors, habits and interests more legible to corporations and governments. But most of the time, that data is hidden from us unless we go digging for it. Even then, we have to know how and where to look. And we almost never get to see how the algorithms work, based on whatever parameters, features, weights and preferences engineers design into the system. That’s all proprietary — the secret sauce.

 

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#Taxonomy of Data Scientists | #datascience #skills

#Taxonomy of Data Scientists | #datascience #skills | e-Xploration | Scoop.it
This is a first attempt at classifying data scientists. I invite you to produce a more comprehensive, better solution.

The 10 pioneering data scientists liste…
luiy's insight:

Who is the purest data scientist?

 

Vincent Granville compares the 4-skill mix of each of these 10 data scientists (as found in the above table), with the generic data science skill mix identified in the previous article (Data Science = 0.24 * Data Mining + 0.15 * Machine Learning + 0.14 * Analytics + 0.11 * Big Data). In short, I computed 10 correlations (one per data scientist) to determine who best represents data science.

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

Les #robots sur le Web social: état des lieux et #prospectives / via @LesDiplomates | #socialbots | e-Xploration | Scoop.it
Des robots avancés ont désormais infiltré les réseaux sociaux et peuvent interagir et tromper les êtres humains. Quelle impact sur les métiers du numérique?
luiy's insight:

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

 

 

Etat des lieux des robots à l’heure actuelle

 

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

 

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

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Mapping Internet #Governance | #cyberdemocracy #SNA

Mapping Internet #Governance | #cyberdemocracy #SNA | e-Xploration | Scoop.it
A collaborative map of processes that shape the evolution of the Internet
luiy's insight:

Already a pressing global issue, internet governance debates are taking place across a range of different fora often referred to as an ecosystem. With the revelations of mass government surveillance, the frequency, intensity, and stakes of internet governance debates have heightened in the last year and this trend promises to continue. At the core of such debates is the future of fundamental rights, such as freedom of expression, privacy, access to knowledge, and access to affordable internet, but also how to decision-making process can become more open, transparent, participatory, accountable, and democratic.

 

Mapping Internet Governance, a collective data compiling and mapping project, traces the relations between the internet governance events, processes, and organizing institutions. The map covers the past 2 years with an effort to better focus civil society advocacy by understanding where main discussions about global internet governance are taking place.

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Hacking public-facing data visualizations at #Twitter / @philogb | #dataviz #ddj

Hacking public-facing visualizations at Twitter Nicolas Garcia Belmonte / @philogb

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Where was Ferguson in my Facebook feed? | #algorithms #filtering

Where was Ferguson in my Facebook feed? | #algorithms #filtering | e-Xploration | Scoop.it
There were big differences in the content related to Ferguson on Twitter and Facebook. Was the reason what users wanted from each, or the sites' algorithms?
luiy's insight:

A number of journalists and commentators observed a jarring disconnect between the mostly uncontroversial posts on Facebook (like chatter about celebrities taking the Ice Bucket Challenge to raise funds for the fight against Lou Gehrig’s disease), and the stream of visceral reportage from the tense scene in Ferguson, where citizens had gathered to protest the August 9th police killing of an unarmed black teen, Michael Brown.

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Chorus Project : #Twitter #analytics tool suite | #bigdata

Chorus Project : #Twitter #analytics tool suite | #bigdata | e-Xploration | Scoop.it
Twitter data retrieval and visual analytics. Designed for social research. GUI based for easy access and fast productivity.
luiy's insight:

The Chorus package currently comprises of two distinct programs:

Tweetcatcher

Firstly, we have Chorus-TCD (TweetCatcher Desktop). Tweetcatcher allows users to sift Twitter for relevant data in two distinct ways: either by topical keywords appearing in Twitter conversation widely (i.e. semantically-driven data) or by identifying a network of Twitter users and following their daily ‘Twitter lives’ (i.e. user-driven data).

Tweetvis

Secondly, we have Chorus-TV (TweetVis), which is a visual analytic suite for facilitating both quantitative and qualitative approaches to social media data in social science. Visual analytics (VA) is an interdisciplinary computing methodology combining methods from data mining, information visualization, human-computer interaction and cognitive psychology. The VA approach is highly relevant to the aims of Chorus, enabling exploratory analysis of social media data in an intuitive and user-friendly fashion. Two main views are available within Chorus-TV. The Timeline Explorer (below) provides users an opportunity to analyse Twitter data across time and visualize the unfolding Twitter conversation according to various metrics (including tweet frequency, sentiment, semantic novelty and homogeneity, collocated words, and so on).

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Mapping the global #Twitter heartbeat: The geography of Twitter | #datascience

Mapping the global #Twitter heartbeat: The geography of Twitter | #datascience | e-Xploration | Scoop.it
Mapping the global Twitter heartbeat: The geography of Twitter
luiy's insight:

In just under seven years, Twitter has grown to count nearly three percent of the entire global population among its active users who have sent more than 170 billion 140–character messages. Today the service plays such a significant role in American culture that the Library of Congress has assembled a permanent archive of the site back to its first tweet, updated daily. With its open API, Twitter has become one of the most popular data sources for social research, yet the majority of the literature has focused on it as a text or network graph source, with only limited efforts to date focusing exclusively on the geography of Twitter, assessing the various sources of geographic information on the service and their accuracy. More than three percent of all tweets are found to have native location information available, while a naive geocoder based on a simple major cities gazetteer and relying on the user–provided Location and Profile fields is able to geolocate more than a third of all tweets with high accuracy when measured against the GPS–based baseline. Geographic proximity is found to play a minimal role both in who users communicate with and what they communicate about, providing evidence that social media is shifting the communicative landscape

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Report: #Bot traffic is up to 61.5% of all website traffic | #scrapers #agents

Report: #Bot traffic is up to 61.5% of all website traffic | #scrapers #agents | e-Xploration | Scoop.it

Bot traffic is up to 61.5% of all website traffic. Who's up, who's down and is Google really winning its war on spam?

luiy's insight:

Research Methodology

 

For the purpose of this report we observed 1.45 Billion visits, which occurred over a 90 day period. The data was collected from a group of 20,000 sites on Incapsula’s network, which consists of clients from all available plans (Free to Enterprise). Geographically, the traffic covers all of the world’s 249 countries, per country codes provided by an ISO 3166-1standard.

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#Complexity in Social Networks | #algorithms #SNA

#Complexity in Social Networks | #algorithms #SNA | e-Xploration | Scoop.it
How network structure impacts consumer experience.
luiy's insight:

In the same way software has “eaten” many industries and continues to devour more, the structure of complex systems is relevant in an increasing number of subjects, from neurobiology to industrial engineering. In the consumer internet, many of the most interesting technology platforms are, at their core, networks. As with most complex systems, small changes can have large consequences, and the structure of a network can materially impact consumer experience, many times changing the core way that people interact with the service.

 

One way to think about these technology platforms is to think of any complex network as having four fundamental components:

 

- Nodes (the objects in the graph, e.g., people, things)

 

- Data/content (the thing being shared between the nodes, e.g., tweet

 

- Edges with rules (e.g., bidirectional “friend”, single-directional “follow”)

 

- Jumping functions, specifically ways to transmit the data/content from one subgroup of people to another on the same platform, usually based on rules surrounding how the edges are structured (e.g., retweeting / liking / favoriting).

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#BIGDATA SOCIETY: Age of Reputation or Age of Discrimination? | #controverses #privacy

#BIGDATA SOCIETY: Age of Reputation or Age of Discrimination? | #controverses #privacy | e-Xploration | Scoop.it
luiy's insight:

Like every technology, Big Data has some side effects. Even if you are not concerned about losing your privacy, you should be worried about one thing: discrimination. A typical application of Big Data is to distinguish different kinds of people: terrorists from normal people, good from bad insurance risks, honest tax payers from those who don't declare all income ... You may ask, isn't that a good thing? Maybe on average it is, but what if you are wrongly classified? Have you checked the information collected by the Internet about your name or gone through the list of pictures google stores about you? Even more scary than how much is known about you is the fact that there is quite some information in between which does not fit. So, what if you are stopped by border control, just because you have a similar name as a criminal suspect? If so, you might have been traumatized for quite some time.

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What's (technically) in your tweets? | #datascience #API #twitter

What's (technically) in your tweets? | #datascience #API #twitter | e-Xploration | Scoop.it
Just because you only see 140 characters doesn't mean that Twitter isn't getting complicated behind the scenes. Here's how status objects are evolving.
luiy's insight:

.. an interesting map of what's going on behind your Twitter stream. As it turns out, there is quite a bit of data associated with not just you as a user, but also with every tweet that you post to the service.

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#Mining the Social Web, 2nd-Edition | #datascience #SNA #tools

#Mining the Social Web, 2nd-Edition | #datascience #SNA #tools | e-Xploration | Scoop.it
Mining-the-Social-Web-2nd-Edition - The official online compendium for Mining the Social Web, 2nd Edition (O'Reilly, 2013)
luiy's insight:

Chapter 0 - Preface

 

Chapter 1 - Mining Twitter: Exploring Trending Topics, Discovering What People Are Talking About, and More

 

Chapter 2 - Mining Facebook: Analyzing Fan Pages, Examining Friendships, and More

 

Chapter 3 - Mining LinkedIn: Faceting Job Titles, Clustering Colleagues, and More

 

Chapter 4 - Mining Google+: Computing Document Similarity, Extracting Collocations, and More

 

Chapter 5 - Mining Web Pages: Using Natural Language Processing to Understand Human Language, Summarize Blog Posts and More

 

Chapter 6 - Mining Mailboxes: Analyzing Who's Talking To Whom About What, How Often, and More

 

Chapter 7 - Mining GitHub: Inspecting Software Collaboration Habits, Building Interest Graphs, and More

 

Chapter 8 - Mining the Semantically Marked-Up Web: Extracting Microformats, Inferencing Over RDF, and More

 

Chapter 9 - Twitter Cookbook

 

Appendix A - Virtual Machine Experience

Appendix B - OAuth Primer

Appendix C - Python & IPython Notebook Tips

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Creating a #heatmap with Photoshop (for #NodeXL) | #SNA #gephi

Creating a #heatmap with Photoshop (for #NodeXL) | #SNA #gephi | e-Xploration | Scoop.it
luiy's insight:

The method presented here shows how to manually create a heatmap of any given NodeXL network with Photoshop. Since this is not an automated process, you can actually create a heatmap out of everything (if you have enough time and creativity). For example an “infrared-image” of a human person:

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How To Detect #Communities Using Social Network Analysis | #SNA

How To Detect #Communities Using Social Network Analysis | #SNA | e-Xploration | Scoop.it
luiy's insight:

Think of communities as very similar to the segments identified in a brand’s customer segmentation model. (With demographics analysis layered on, you might even find that they’re the same.)

While direct marketing communications is often customized by segment, historically this hasn’t been something brands have done in social. But, using social network analysis and also Twitter & Facebook ad targeting, it’s possible to send specific messages to specific groups of people.

 

Powered by Pulsar TRAC these could be people engaging in a specific conversation, individuals sharing a piece of content online, or the followers of an account on Twitter. Any group of people, in essence, as long as we can define that audience through some property of its behaviour in social media – such as keyword, user bio, or location.

 

Community analysis allows brands to really understand the behavior of their audiences in a way they can’t replicate with offline, non-social data.

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Why #d3 Will Change How We Publish #Maps | #dataviz

Why #d3 Will Change How We Publish #Maps | #dataviz | e-Xploration | Scoop.it
Publishing maps to the web. Simple right? Just reproject all your data to web mercator and be done with it. Have we all learned to live with the crazy distortion? Do we need mercator to help us...
luiy's insight:

D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG and CSS. D3’s emphasis on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework, combining powerful visualization components and a data-driven approach to DOM manipulation.

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US #CyberWarriors battling Islamic State on Twitter | #trolling #strategies

US #CyberWarriors battling Islamic State on Twitter | #trolling #strategies | e-Xploration | Scoop.it
The United States has launched a social media offensive against the Islamic State and Al-Qaeda, setting out to win the war of ideas by ridiculing the militants with a mixture of blunt language and sarcasm.

Via Ángel G. de Ágreda
luiy's insight:

The US-managed Twitter accounts are also not squeamish about reproducing images distributed by jihadists depicting mass executions, drawing historic parallels between Islamic State militants and the Nazis.

 

One post showed armed Islamic State fighters standing over a ditch filled with executed people, alongside another almost identical image of Nazis killing people in similar circumstances.

 

"Then & Now: Nazis – like ISIS – murdered out of intolerance, hatred, zeal," read a comment alongside the two images.

 

Satire is also used to undermine militants, with one re-tweeted cartoon referring to the "ISIS bucket challenge" featuring a participant named as "the civilized world" being drenched by a bucket of blood.



Read more at: http://phys.org/news/2014-08-cyber-warriors-islamic-state-twitter.html#jCp

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Annotation Studio: suite of #collaborative web-based annotation #tools | #DH

Annotation Studio: suite of #collaborative web-based annotation #tools | #DH | e-Xploration | Scoop.it
luiy's insight:

Annotation Studio in the Digital Humanities

 

The most significant difference between Annotation Studio and other digital annotation projects is its emphasis on student-centered design and pedagogy. Most other annotation tools assume user familiarity with TEI, and a well-developed understanding of the relationships between literary sources, manuscripts, editions, and adaptations. Annotation Studio makes sophisticated yet easy-to-use commenting tools immediately accessible to students with no prior experience with close textual analysis or TEI.

 

However, while we believe Annotation Studio provides many unique affordances, we also see it as part of a larger conversation concerning annotation in the digital humanities. Accordingly, we have listed what we think are some of the most exciting projects occupying the annotation space, which bear both similarities and differences to the aims and formal qualities of our tool.

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Social Media and the ‘Spiral of Silence’ | #surveillance #privacy

Social Media and the ‘Spiral of Silence’ | #surveillance #privacy | e-Xploration | Scoop.it
Facebook, Twitter, and other platforms did not provide new outlets for the discussion of the Snowden-NSA revelations. People who thought their social media friends disagreed with them were less likely to discuss the issues in person and online.
luiy's insight:

An informed citizenry depends on people’s exposure to information on important political issues and on their willingness to discuss these issues with those around them. The rise of social media, such as Facebook and Twitter, has introduced new spaces where political discussion and debate can take place. This report explores the degree to which social media affects a long-established human attribute—that those who think they hold minority opinions often self-censor, failing to speak out for fear of ostracism or ridicule. It is called the “spiral of silence.”

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Analyse de #sentiments automatique, pourquoi est-ce si compliqué ? | #datascience #lexicometric

Analyse de #sentiments automatique, pourquoi est-ce si compliqué ? | #datascience #lexicometric | e-Xploration | Scoop.it

A l’heure où le big data représente l’un des grands défis technologiques et économiques actuels, de nombreux outils d’analyse se positionnent sur le marché afin d’offrir aux entreprises une connaissance clients davantage poussée.

luiy's insight:

Certaines techniques actuelles font appel à des traitements lexicométriques, mêlant analyses linguistiques et statistiques. D’autres s’appuient sur des techniques d’apprentissage automatique afin d’améliorer automatiquement les performances des programmes d’analyse au fur et à mesure de leur utilisation.

 

Quelle que soit la méthode utilisée, toutes les subtilités du langage ne peuvent être reconstituées sous forme d’algorithmes pour être reconnues par un système informatique. En effet, la langue comprend différents niveaux d’articulation, chaque niveau comportant son lot de difficultés :

 

- Niveau lexical

- Niveau syntaxique

- Niveau sémantique

- Niveau pragmatique

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#Bigdata, language and the death of the theorist | #DH #algorithms

#Bigdata, language and the death of the theorist | #DH #algorithms | e-Xploration | Scoop.it
Plenty of people have foreseen the death of the scientific theory at the hands of big data analysis, but when computers become good enough to understand literature, art and human history, will it spell the end for the humanities academic?
luiy's insight:

A lot has been written about the ways that big data has changed scientific enquiry, but as supercomputers increase in power and the tools to use them become less obtuse, whole new academic disciplines are beginning to feel the benefits of crunching data.

 

Believe it or not, some people even think we can forecast the future with big data. Predicting world-changing events is a possibility, some claim, if you treat society and history like a big data problem. It's how big data analyst Kalev Leetaru found where Osama bin Laden had been hiding, in a way.

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