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antropologo.net, dataviz, collective intelligence, algorithms, social learning, social change, digital humanities
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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, 2014 6:12 PM

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

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Every #datajournalism book since 1970: interactive timeline | #ddj

Every #datajournalism book since 1970: interactive timeline | #ddj | e-Xploration | Scoop.it
Guide to data journalism in books, from 1970 to 2012
luiy's insight:

Dutch investigative reporter Henk van Ess has created this guide to data journalism in books, from 1970 to 2012. It shows how the field has changed, from 'precision reporting' to 'computer assisted reporting' to 'data journalism'. Oh and it includes our book, Facts are Sacred: the power of data (on Kindle) and the latest Data Journalism Handbook. Who is it missing?

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Is ‘massive open online #research’ #MOOR the next frontier for #education? | #MOOC

Is ‘massive open online #research’ #MOOR the next frontier for #education? | #MOOC | e-Xploration | Scoop.it
UC San Diego is launching the first major online course that prominently features massive open online research (MOOR). In “Bioinformatics Algorithms
luiy's insight:

UC San Diego is launching the first major online course that prominently features “massive open online research” (MOOR).

 

In “Bioinformatics Algorithms — Part 1,” UC San Diego computer science and engineering professor Pavel Pevzner and his graduate students are offering a course on Coursera that combines research with a MOOC (massive open online course) for the first time.

 

“All students who sign up for the course will be given an opportunity to work on specific research projects under the leadership of prominent bioinformatics scientists from different countries, who have agreed to interact and mentor their respective teams.”

 

“The natural progression of education is for people to make a transition from learning to research, which is a huge jump for many students, and essentially impossible for students in isolated areas,” said Ph.D. student Phillip Compeau, who helped develop the online course. “By integrating the research with an interactive text and a MOOC, it creates a pipeline to streamline this transition.”

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selfiecity : Investigating the style of self-portraits (selfies) | #dataviz #research

selfiecity : Investigating the style of self-portraits (selfies) | #dataviz #research | e-Xploration | Scoop.it

Investigating the style of self-portraits (selfies) in five cities across the world.

luiy's insight:

Investigating the style of self-portraits (selfies) in five cities across the world.

 

Selfiecity investigates selfies using a mix of theoretic, artistic and quantitative methods:

 

We present our findings about the demographics of people taking selfies, their poses and expressions. 

 

Rich media visualizations (imageplots) assemble thousands of photos to reveal interesting patterns. 

 

The interactive selfiexploratory allows you to navigate the whole set of 3200 photos. 

 

Finally, theoretical essays discuss selfies in the history of photography, the functions of images in social media, and methods and dataset.

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#Collaborative #research and mapping for Nairobi’s #Public Transit | #urban #CI

#Collaborative #research and mapping for Nairobi’s #Public Transit | #urban #CI | e-Xploration | Scoop.it
Default Text
luiy's insight:
Collaborative research and mapping for Nairobi’s Public Transit

University of Nairobi, Columbia University’s Center for Sustainable Urban Development , MIT’s Civic Data Design Lab , and Groupshot are working toward standardizing and opening transit data for Nairobi’s Matatus — the informal and de facto city bus system — and expanding our findings, tools, and processes globally. Building on past Kenyan-based digital mapping efforts and open source transit software, the group will produce a comprehensive framework for collecting, opening and mapping Matatu transportation data toward a mobile and equitable Nairobi.

 

Currently underway, a primary round of data collection and local student design workshops are growing the understanding of this otherwise misunderstood and complex system. The first series of tools will be entering development this spring to improve on data collection and transport information management in the decentralized Matatu system. This project uses Nairobi’s active mobile phone community to develop a standardized Matatu bus route for Nairobi informal buses. By developing crowd sourcing applications we hope people in Nairobi can develop, contribute, maintain and own their own transit information.

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White Paper on Research #Challenges in Social #CollectiveIntelligence


Via Pierre Levy
luiy's insight:

This report first situates and outlines the potential of social computation to provide the basis for Social Collective Intelligence (SCI) in future systems. This involves the close interaction of social groups and machines together with systems of incentives and social structures to perform tasks that would otherwise be difficult to achieve either using entirely human or entirely machine solutions. The deliverable considers the challenges both from a technical and from a social science standpoint, identifying the potential for aligning them in order to provide an interdisciplinary perspective on the development of SCI systems. The paper then describes some of the challenges in developing an engineering approach to the development of such systems. Finally the paper outlines some of the “big questions” that arise from the framework for SCI research developed in the white paper.

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Rescooped by luiy from Homo Agilis (Collective Intelligence, Agility and Sustainability : The Future is already here)
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COLLECTIVE INTELLIGENCE IN HUMANS: A LITERATURE REVIEW (2012) | #CI


Via Claude Emond
luiy's insight:

A sample of literature discussing the collective intelligence in humans was reviewed and the discovered themes were categorized into micro-level, macro-level and emergence-level phenomena. The framework is similar to the conceptual model of Luo et al. (2009), the gist of which is the question of how macro-level phenomena emerge from micro-level interactions. The framework proposed in this paper emerged from data collected from contemporary literature. Therefore, it is arguable that the scientific community has already implicitly divided collective intelligence to the aforementioned three levels of abstraction. Making this division explicit hopefully brings some structure to the discussion and helps in fitting the pieces of the puzzle together. The categorization of themes related to collective intelligence (Table 1) provides guidance for selecting topics for further literature reviews and suggests how the results might fit into the big picture of collective intelligence in humans. 

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Claude Emond's curator insight, January 18, 2014 11:01 PM

Another paper from the proceedings of Collective Intelligence 2012 (http://www.ci2012.org/) . Good up to date literature review in English

Claude Emond's comment, January 19, 2014 5:42 PM
very interesting comment Luis. I am learning quite a few things here
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More Than 800,000 Scientific Papers In One Beautiful Infographic | #scientometrics #SNA

More Than 800,000 Scientific Papers In One Beautiful Infographic | #scientometrics #SNA | e-Xploration | Scoop.it

ArXiv is an online archive that stores hundreds of thousands of scientific papers in physics, mathematics, and other fields. The citations in those papers link to one another, forming a web, but you're not going to see those connections just by sifting through the archive.

So physicist Damien George and Ph.D student Rob Knegjens took it on themselves to create Paperscape, an interactive infographic that beautifully and intuitively charts the papers.

The infographic is a mass of circles. Each circle represents a paper, and the bigger a circle is, the more highly cited it is. The papers are color-coded by discipline--pink for astrophysics, yellow for math, etc.--and papers that share many of the same citations are placed closer together.


Via Lauren Moss
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Jay Ratcliff's curator insight, September 6, 2013 1:35 PM

This is cool!  It is like the map of the Internet done last year sometime.

I lucked out and found the section about SNA in the lower left hand side of the map.  Look for Network under the Quantitative Finance section, go figure.

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Investigación y desarrollo. Research and consulting. - Gephi Marketplace @luiy

Investigación y desarrollo. Research and consulting. - Gephi Marketplace @luiy | e-Xploration | Scoop.it
luiy's insight:

Gephi Marketplace @luiy


Design and development of services and products about knowledge analysis with Gephi.


- Collaboration analysis
- Organizations dynamics
- Learning analytics
- Knowledge management
- Social media analysis
- Roles and profiles
- Scientometrics
- Ethnographic models

 

Home page: http://viz.oycib.org/

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Data Visualization: Communication & Creativity

Data Visualization: Communication & Creativity | e-Xploration | Scoop.it

Visual communication skills are alien to some in the research industry, but they needn’t be. Data visualisation can become part of the research process through smart hiring, skills training and expert partnerships.


Data visualisation should not be regarded as an end in itself; the real point to data visualisation - the value that it brings to research buyers and suppliers - is as an aid to storytelling. It’s about seeing the patterns in the data that flush out a story and then help you to start telling that story. Only by doing that can you move data off the spreadsheet and out into the real world of consumer behaviour and preferences.

The best analogy and the one used frequently, is with journalism. It’s no surprise either that many great examples of data visualisation come from the publishing and media sectors. Journalists face the same challenge that we do of sifting large amounts of often conflicting data to arrive at a truth or an insight...


Via Lauren Moss
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Lauren Moss's curator insight, January 8, 2013 4:23 PM

An interesting look at the current role of data visualization and data journalism in the advancement of research, communication, and brand development.

Scott Turner's curator insight, January 9, 2013 8:31 AM

An interesting look at the current role of data visualization and data journalism in the advancement of research, communication, and brand development.

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Human #CollectiveIntelligence under Dual Exploration-Exploitation Dilemmas | #CI #research

PLOS ONE: an inclusive, peer-reviewed, open-access resource from the PUBLIC LIBRARY OF SCIENCE. Reports of well-performed scientific studies from all disciplines freely available to the whole world.
luiy's insight:

We investigated experimentally whether social learning opportunities might improve the performance of human participants working on a “multi-armed bandit” problem in groups, where they could learn about each other's past choice behaviors. Results showed that, even though information scroungers emerged frequently in groups, social learning opportunities reduced total group exploration time while increasing harvesting from better options, and consequentially improved collective performance. Surprisingly, enriching social information by allowing participants to observe others' evaluations of chosen options (e.g., Amazon's 5-star rating system) in addition to choice-frequency information had a detrimental impact on performance compared to the simpler situation with only the choice-frequency information. These results indicate that humans groups can handle the fundamental “dual exploration-exploitation dilemmas” successfully, and that social learning about simple choice-frequencies can help produce collective intelligence.

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K-CORE DECOMPOSITION OF INTERNET GRAPHS: HIERARCHIES, SELF-SIMILARITY AND MEASUREMENT BIASES | #datascience #SNA

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#Gephi plugin for depth-first searching for closed cycles on graphs | #SNA

#Gephi plugin for depth-first searching for closed cycles on graphs | #SNA | e-Xploration | Scoop.it
This free plugin for gephi traverses the active graph searching for closed walks, cycles and cliques. It can be used on both directed and undirected graphs.
luiy's insight:

This Gephi plugin traverses the active graph searching for closed walks, cycles and cliques. The search is made using the popular depth-first order search algorithm, using a standard single stack implementation made popular by Robert Sedgewick. Although this is very common in graph searching, there wasn’t a plugin for Gephi performing just this simple task and no more in a efficient way. Some features:

 

The plugin can be used on both directed and undirected graphs. In the first case, close walks (cycles) are hunted, while cliques in the latter; Reports include a distribution of the founded cycles by size; No use of external libraries: just 18k for the whole package; Asynchronous and interruptible task; Written in a pure OOP flavour, using Gephi APIs.
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Constraints on the Universe as a Numerical #Simulation | #research #algorithms

Constraints on the Universe as a Numerical #Simulation | #research #algorithms | e-Xploration | Scoop.it
luiy's insight:

Observable consequences of the hypothesis that the observed universe is a numerical simulation performed on a cubic space-time lattice or grid are explored. The simulation scenario is first motivated by extrapolating current trends in computational resource requirements for lattice QCD into the future. Using the historical development of lattice gauge theory technology as a guide, we assume that our universe is an early numerical simulation with unimproved Wilson fermion discretization and investigate potentially-observable consequences. Among the observables that are considered are the muon g-2 and the current differences between determinations of alpha, but the most stringent bound on the inverse lattice spacing of the universe, b^(-1) >~ 10^(11) GeV, is derived from the high-energy cut off of the cosmic ray spectrum. The numerical simulation scenario could reveal itself in the distributions of the highest energy cosmic rays exhibiting a degree of rotational symmetry breaking that reflects the structure of the underlying lattice.

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Digital research #tools | #dh

Digital research #tools | #dh | e-Xploration | Scoop.it

Via Pierre Levy
luiy's insight:

This version of DiRT has been superseded by Bamboo DiRT, developed by Quinn Dombrowski and Project Bamboo.  Bamboo DiRT makes several improvements over the old DiRT and is much more current.  No new information will be added here as of 1/9/2012, but this wiki is still available for historical purposes. For more information, please see this message. 


Mew LINK:http://dirt.projectbamboo.org/

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Pierre Levy's curator insight, February 11, 2014 7:39 PM

Extensive trove of resources for digital humanities

sandra alvaro's curator insight, February 12, 2014 5:32 AM

wiki with resources for digital humanities projects

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High-Resolution Maps of Science | #dataviz #scientometrics

High-Resolution Maps of Science | #dataviz #scientometrics | e-Xploration | Scoop.it

'Maps of science derived from citation data visualize the relationships among scholarly publications or disciplines. They are valuable instruments for exploring the structure and evolution of scholarly activity. Much like early world charts, these maps of science provide an overall visual perspective of science as well as a reference system that stimulates further exploration. However, these maps are also significantly biased due to the nature of the citation data from which they are derived: existing citation databases overrepresent the natural sciences; substantial delays typical of journal publication yield insights in science past, not present; and connections between scientific disciplines are tracked in a manner that ignores informal cross-fertilization..'


Via Nicholas Goubert, Lauren Moss, Rui Guimarães Lima
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Comparison of #research networking #tools and research profiling systems

Comparison of research networking tools and research profiling systems - Wikipedia, the free encyclopedia

Importantly, data harvested into robust RN tools is accessible for broad repurposing, especially if available as linked open data (RDF triples). Thus RN tools enhance research support activities by providing data for customized, up-to-date web pages, CV/biosketch generation, and data tables for grant proposals.

luiy's insight:
Contents: 1. General 2. Data Sources, Ingest and Export Formats 3. Data Interoperability and Integration 4. Users Profiled, User Interactivity and Networking Functionality 5. Controlled Vocabulary, Ontologies and Author Disambiguation 6. Bibliometrics
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The role of Twitter in the life cycle of a scientific publication

Twitter is a micro-blogging social media platform for short messages that can have a long-term impact on how scientists create and publish ideas. We investigate the usefulness of twitter in the development and distribution of scientific knowledge.

Via Pierre Levy
luiy's insight:

Many scientists are making the move towards social media in order to accelerate  and amplify their scientific impact (Fausto et al. 2012; Fox 2012; Piwowar 2013). One in 40 scientists is active on Twitter (Priem et al. 2012a), 25,000 blog entries have been indexed on the Research Blogging platform, and 2 million scientists are using Mendeley, a reference sharing tool (Piwowar 2013). Here, we consider 140 how social media, and Twitter in particular, can influence the life cycle of scientific publication, from inception and collaboration on a spark of an idea to the communication of a finished product. Specifically, we evaluate and discuss the benefits of Twitter for (1) increasing scholarly connections and networks, (2) quickly developing ideas through novel collaborations and pre-review, and (3) amplifying the dissemination and discussion of scientific knowledge both within and beyond the ivory tower of academia.

 

 

The impact of scientific papers has traditionally been measured in terms of
numbers of citations (Neylon and Wu 2009). Tweeting can influence this impact metric. For example, articles published in the Journal of Medical Internet Research that were tweeted about frequently in the first three days following publication were 11 times more likely to be highly cited 17 to 29 months later than  less tweeted articles (Eysenbach 2011). In fact, top-cited articles could be predicted quite accurately from their early tweeting frequency (Eysenbach 2011). In a separate study of ~4600 scientific articles published in the preprint database  arXiv.org, Shuai et al. (2012) found that papers with more mentions on Twitter were also associated with more downloads and early citations of papers, although the causality of these relationships is unclear (Shuai et al. 2012).

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Antonio Figueiredo's curator insight, May 19, 2013 4:54 AM

Paper available on PeerJ discusses the role of Twitter in the lifecycle of a scientific publication.

Renato P. dos Santos's curator insight, May 20, 2013 10:07 AM

estudo conclui que o Twitter contribui para a publicação científica no século 21

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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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Visualizing Databases | Digital Humanities Specialist

Visualizing Databases | Digital Humanities Specialist | e-Xploration | Scoop.it

Summaries and statistics drawn from within the structure of the database are not enough. If there is to be any real grappling with the database as an culturally-embedded construct, then it has to be done in a manner that reveals the data, the model and the population simultaneously.


Via Lauren Moss
luiy's insight:

I’ve become quite the fan of Gephi, lately, and received a good-natured challenge by one of my colleagues, which went something like, “Why is a everything a network with you, now?”  Obviously, in the case of social network-like phenomena, such as mapping collaboration in the Digital Humanities with the DH@Stanford graph–network theory and network language (whether visual or theoretical) make sense.  Network analytical tools like Gephi are also only a short step away from spatial analytical tools, like ArcGIS, many of which are used to ask questions about geographic networks and not about the kind of continuous data found in topography.

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