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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 7:26 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.

e-Xploration
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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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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How People Consume #Conspiracy Theories on Facebook | #sna #controverses

How People Consume #Conspiracy Theories on Facebook | #sna #controverses | e-Xploration | Scoop.it
… in much the same way as mainstream readers consume ordinary news, say computer scientists.
luiy's insight:

And that raises an interesting question. How do conspiracy theories spread through the Internet and do people treat these ideas in a way that is fundamentally different to conventional stories from established news organizations?

 

To find out, Alessandro Bessi and pals at the Institute for Advanced Studies in Lucca, Italy, examined the way people on Facebook consume conspiracy theories versus the way they consume mainstream news. And they say there are remarkable similarities but also some interesting differences that may help to better understand the way that false information spreads around the web.

 

The team began by studying over 270,000 posts created on 73 different Facebook pages. They classified these pages according to the kind of information they contained, whether conspiracy news or mainstream scientific news. They also counted the number of likes each post received, a total of almost 10 million, the number of shares, as well as the individuals who contributed.

 

Having divided up the posts, they found that around 60,000 involved mainstream scientific news and over 200,000 involved alternative conspiracy news. And while the scientific news received 2.5 million likes, the alternative news had over 6.5 million likes.

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#SemanadelEmprendedor - México 2014 - Gráficos de conversaciones y Ecosistema | #SNA #gephi

#SemanadelEmprendedor - México 2014 - Gráficos de conversaciones y Ecosistema | #SNA #gephi | e-Xploration | Scoop.it
luiy's insight:

En el contexto del evento #SemanadelEmprendedor 2014 en México desarrollamos y presentamos los siguiente gráficos:

 

- los actores principales que participarón en Twitter en el contexto del evento #SemanadelEmprendedor 2014

 

- los actores principales del Ecosistema Emprendedor 2014 en México.

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New #tool makes online #personaldata more transparent | #privacy

New #tool makes online #personaldata more transparent | #privacy | e-Xploration | Scoop.it
The web can be an opaque black box: it leverages our personal information without our knowledge or control. When, for instance, a user sees an ad about depression online, she may not realize that she is seeing it because she recently sent an email about being sad. Roxana Geambasu and Augustin Chaintreau, ...
luiy's insight:

The tool for revealing personal data use on the Web. It reveals which specific data inputs (such as emails) are used to target which outputs (such as ads). It is general and can track data use both within and across arbitrary Web services. The key idea behind XRay is to detect targeting through black-box input/output correlation. XRay populates a series of extra accounts with subsets of the inputs and then looks at the differences and commonalities between the outputs that they get in order to obtain correlation. This mechanism is effective at detecting certain types of data uses, though not all. For its details, please refer to our research paper, which will appear in August at USENIX Security 2014, a top systems security conference.


http://xray.cs.columbia.edu/

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How Yahoo Research Labs Studies Culture as a Formal Computational Concept | #SNA #DH

How Yahoo Research Labs Studies Culture as a Formal Computational Concept | #SNA #DH | e-Xploration | Scoop.it
The ultimate goal: a truly computational understanding of human society, say Yahoo’s computational anthropologists.
luiy's insight:

Today, Luca Maria Aiello at Yahoo Labs in Barcelona, Spain, and a couple of pals, change that. They tease apart the nature of the links that form on social networks and say these atoms fall into three different categories. They also show how to extract this information automatically and then characterize the relationships according to the combination of atoms that exist between individuals. Their ultimate goal: to turn anthropology into a full-blooded subdiscipline of computer science.

 

Aiello and co used two data sets from a pair of large social networks. The first consists of over 1 million messages sent between 500,000 pairs of users of the aNobii social network, which people use to talk about books they have read. The second is a set of 100,000 anonymized user pairs who commented on each other’s photos on Flickr, sending around 2 million messages in total.

 

The team analyzes these messages based on the type of information they convey, which they divide into three groups. The first type of information is related to social status; messages displaying appreciation or announcing the creation of the social tie such as a follow or like. For example, a user might say a photograph is “an excellent shot” or say they’ve followed somebody or acknowledged attention they’ve got by thanking them for visiting a site.

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Francisco Restivo's curator insight, August 20, 3:51 AM

Alex Pentland would call this Social Physics.

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2014 #Ebola Outbreak: Worldwide Air Transportation and Relative Import #Risk | #dataviz

2014 #Ebola Outbreak: Worldwide Air Transportation and Relative Import #Risk | #dataviz | e-Xploration | Scoop.it

Click here to edit the title

luiy's insight:
The Nodes: Nodes in the network represent the largest 1227 airports in the worldwide air-transportation network (WAN) comprising approx. 95% of the entire global air traffic. The dataset used in our computational models contains more than 4000 airports, a total passenger flux of more than 3 billion passengers/year. Node size quantifies the capacity (size) of an airport. Colors correspond to geographical regions. Hover over a node for an additional info pop-up.
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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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Online collaboration: Scientists and the social network | #science #socialmedia

Online collaboration: Scientists and the social network | #science #socialmedia | e-Xploration | Scoop.it
Giant academic social networks have taken off to a degree that no one expected even a few years ago. A Nature survey explores why.
luiy's insight:

The results confirm that ResearchGate is certainly well-known (see ‘Remarkable reach’, and full results online at go.nature.com/jvx7pl). More than 88% of scientists and engineers said that they were aware of it — slightly more than had heard of Google+ and Twitter — with little difference between countries. Just under half said that they visit regularly, putting the site second only to Google Scholar, and ahead of Facebook and LinkedIn. Almost 29% of regular visitors had signed up for a profile on ResearchGate in the past year.

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Francisco Restivo's curator insight, August 23, 3:12 PM

Scientists and social scientists use social networks differently. But they use!

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#Privacy, Anonymity, and #BigData in the Social Sciences | #dh #MOOC

#Privacy, Anonymity, and #BigData in the Social Sciences | #dh #MOOC | e-Xploration | Scoop.it
A recent article suggests that open science may be irreconcilable with anonymous data, requiring a reconsideration of how we protect privacy in educational data.
luiy's insight:

The short version: many people have called for making science more open and transparent by sharing data and posting data openly. This allows researchers to check each other's work and to aggregate smaller datasets into larger ones. One saying that I'm fond of is: "the best use of your dataset is something that someone else will come up with." The problem is that increasingly, all of this data is about us. In education, it's about our demographics, our learning behavior, and our performance. Across the social sciences, it's about our health, our beliefs, and our social connections. Sharing and merging data adds to the risk of disclosing those data. 

 

The article shares a case study of our efforts to strike a balance between anonymity and open science by de-identifying a dataset of learner data from HarvardX and releasing it to the public. In order to de-identify the data to a standard that we thought was reasonably resistant to reidentification efforts, we had to delete some records and blur some variables. If a learner's combination of identifying variables was too unique, we either deleted the record or scrubbed the data to make it look less unique. The result was suitable for release (in our view), but as we looked more closely at the released dataset, it wasn't suitable for science. We scrubbed the data to the point where it was problematically dissimilar from the original dataset. If you do research using our data, you can't be sure if your findings are legitimate or an artifact of de-identification. 

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Net Neutrality, #Algorithmic Filtering and #Ferguson | #censorship

Net Neutrality, #Algorithmic Filtering and #Ferguson | #censorship | e-Xploration | Scoop.it

Net Neutrality, Algorithmic Filtering and Ferguson

luiy's insight:

Twitter was also affected by algorithmic filtering. “Ferguson” did not trend in the US on Twitter but it did trend locally. [I’ve since learned from @gilgul that that it *briefly* trended but mostly trended at localities.] So, there were fewer chances for people not already following the news to see it on their “trending” bar. Why? Almost certainly because there was already national, simmering discussion for many days and Twitter’s trending algorithm (said to be based on a method called “term frequency inverse document frequency”) rewards spikes… So, as people in localities who had not been talking a lot about Ferguson started to mention it, it trended there though the national build-up in the last five days penalized Ferguson.


Algorithms have consequences.


Mass media, typically, does not do very well covering chronic problems of unprivileged populations, poor urban blacks bear the brunt of this, but they are not alone. Rural mostly white America, too, is almost always ignored except for the occasional “meth labs everywhere” story. But yesterday, many outlets were trying, except police didn’t let them. Chris Hayes says that police ordered satellite trucks off the area so that they could not go live from the area. Washington Post was only one outlet whose journalists were arrested — citizen journalists were targeted as well.


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#Naoyun – Visualize Live Twitter Activity | #SNA #gephi

#Naoyun – Visualize Live Twitter Activity | #SNA #gephi | e-Xploration | Scoop.it
luiy's insight:

The TwitterStreamer is the main class that manage the Twitter API . This class also load a class that extends TwitterGephiStreamer. Each time the Twitter Api get a new Status, the TwitterStreamer call the newStatus method from the TwitterGephiStreamer class.

On this method, there is the « Network Logic ». I called « Network Logic » all the processes and the rules to create a network from Twitter status.

 

For the moment, Naoyun have 3 network logic :

 

- TwittFullGrapher : Makes a complete graph by representing users, hashtags, tweet, media, links and their connection. The « Smart » version implemented in Naoyun won’t represent tracked hashtag to improve the visibility of the graph.


- TwitterUserNetwork : Represent only the relation between users.


- GeoTwitt : Just display Twitt with Geo localisation

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Le numérique réinvente la consommation culturelle | #DH #musées

Le numérique réinvente la consommation culturelle | #DH #musées | e-Xploration | Scoop.it
Musées en ligne, création artistique digitale, e-commerce de l'art... la multiplication des expériences numériques dans le monde de la culture recoupe des réalités fort diverses. Et la nébuleuse des initiatives rend la lecture de ce secteur naissant éminemment complexe. Comment repenser l'offre culturelle à l'heure de sa dématérialisation ? Comment répondre aux nouveaux besoins d'un « consommateur » d'art ultra-connecté ?
luiy's insight:

S'appuyant justement sur l'interaction visiteur et l'expérience immersive, le Centre Pompidou a lancé « Éduque le Troll », en 2012, son premier Alternate Reality Game (ARG). Ces jeux en réalité alternée aux fonctions pédagogiques et ludiques sont fort prisés des musées. Il en est de même pour les serious games, jeux intelligents interactifs développés par les châteaux de Versailles et de Fontainebleau. Le transmédia a également la faveur des lieux patrimoniaux.

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How Google and Twitter move the #market for #bitcoin | #economy #cyberculture

How Google and Twitter move the #market for #bitcoin | #economy #cyberculture | e-Xploration | Scoop.it
luiy's insight:

Anyone who has followed bitcoin over the last three years knows that its price is an ad nauseum repeat of price spikes followed by mini crashes. Some of them have been triggered by external stimuli, like MtGox being hacked in 2011 before it ultimately met its demise this past March. The cycle — more like a roller coaster — of bitcoin price movements is becoming an interesting research topic for academics. However, how much of the price fluctuation has to do with the hype around the cryptocurrency?

Researchers at ETH Zurich, a university in Switzerland, decided to study how social information online affected the price in their paper:

 

“The digital traces of bubbles: feedback cycles between socio economic signals in the bitcoin economy.” http://arxiv.org/abs/1408.1494

 

The researchers looked at Facebook shares, number of tweets, number of downloads of the blockchain client, users on the network and the number of searches on both Google and Wikipedia to try to find a correlation between the price and the online network.

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