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While SOPA and PIPA are no laughing matter (join the strike), the reaction from those on Twitter who don't know what's going on is great entertainment. Do a search on 'wtf wikipedia' for tweets from confused individuals who are trying to find information on stuff. I'm just going to leave Twitter trackers Revisit and Spot, by Moritz Stefaner and Jeff Clark, respectively, open all day. "OMG I'm doing homework and Wikipedia is blacked out wtf !!!!!!!!!!!!!!!!!!!!!"
Whenever you look at an item on Amazon, the site recommends related items that you might be interested in. So in a way, these items are connected by how people buy. Artist and designer Christopher Warnow uses the metaphor to create a network of Amazon products, where each node represents an item, and connections, or edges, represent common bonds of recommendations. Simply enter an Amazon link, and Warnow's software generates a network.
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Twitter is an organic online location, full of retweets, conversations, and link sharing. Jeff Clark tries to show these inner workings with his newest interactive, Spot. Enter a query in the field on the bottom left, and Spot retrieves the most recent 200 tweets. You then can choose among five views: group, words, timeline, users, and source.
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While we're on the topic of academic papers and how they're linked, Johan Bollen et. al used clickstream data to draw detailed maps of science, from the point of view of those actually reading the papers. That is, instead of relying on citations, they used log data on how readers request papers, in the form of a billion user interactions on various web portals.
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.
Cross-fertilization. Saucy.
Each circle represents a journal and edges represent connections between journals, according to Johan Bollen et. al's clickstream model. Circles are color-coded by journal classifications from the Getty Research Institute's Art and Architecture Thesaurus.
So you have most of the engineering and physical sciences on the perimeter, medical-related areas to the left, and liberal arts is that middle cluster. Statistics is towards the top left, mixed in with demographics, philosophy, and sociology. There aren't many surprises in the clusters, but there are interesting, albeit weaker, links in the open spaces, such as religion and chemistry or music and ecology.
[PLoS ONE | Thanks, @drewconway]
From Autodesk Research, Citeology is an interactive that visualizes connections in academic research via paper citations:
The names of each of the 3,502 papers published at the CHI and UIST Human Computer Interaction (HCI) conferences between 1982 and 2010 are listed by year and sorted with the most cited papers in the middle. In total, 11,699 citations were made from one article to another within this collection. These citations are represented by the curved lines in the graphic, linking each paper to those that it referenced.
The interactive repsonds slowly to clicks and only works in Firefox for me, but it's interesting to play around even if you aren't familiar with CHI and HCI papers. It works better if you select one to three generations instead of all. Click on a specific paper and you get citations for that paper on the right (brown) and the papers that the selected cited on the left (blue).
Color-coding for categories, authors, or subject could add another level of meaning to this. For example, do we see the subject evolve? Do papers that focus on a certain subject site outside of the main topic?
[Citeology via infosthetics]
Food flavors across cultures and geography vary a lot. Some cuisines use a lot of scallion and ginger, whereas another might use a lot of onion and butter. Then again, everyone seems to use garlic. Yong-Yeol Ahn, et al. took a closer look at what makes food taste different, breaking ingredients into flavor compounds and examining what the ingredients had in common. A flavor network was the result:
Each node denotes an ingredient, the node color indicates food category, and node size reflects the ingredient prevalence in recipes. Two ingredients are connected if they share a significant number of flavor compounds, link thickness representing the number of shared compounds between the two ingredients. Adjacent links are bundled to reduce the clutter.
Mushrooms and liver are on the edges, out on their lonesome.
[Nature | Thanks, Elise]
During the riots in London this past summer, a lot of information spread quickly about what was going on. Some of that information was true and some was not so true. The Guardian explores this spread of information on Twitter, and how fact and fiction seem to reveal themselves on their own:
A period of unrest can provoke many untruths, an analysis of 2.6 million tweets suggests. But Twitter is adept at correcting misinformation - particularly if the claim is that a tiger is on the loose in Primrose Hill.
Other rumors include when rioters cooked their own food at McDonald's (false), London Eye was set on fire (false), and Miss Selfridge was set on fire (true).
Each bubble represents a tweet and is sized by number of followers the tweeter has. The big one is usually the orignal tweet and the small ones that cluster around are retweets. Then the colors represent tweets that support, oppose, question, or comment. So when you play the animation for each rumor, bubbles swiftly pop up at the rumor peaks and then settle at true or false.
You can also use the scroll to move to a certain point in time, and roll over bubbles to see the tweets.
Really nice graphic and worth a look.
[Guardian via @jakeporway]
Hilary Mason, chief scientist at bitly, examined links to 600 science pages and the pages that those people visited next:
The results revealed which subjects were strongly and weakly associated. Chemistry was linked to almost no other science. Biology was linked to almost all of them. Health was tied more to business than to food. But why did fashion connect strongly to physics? And why was astronomy linked to genetics?
The interactive lets you poke around the data, looking at connections sorted from weakest (fewer links) to strongest (more links), and nodes are organized such that topics with more links between each other are closer together.
Natural next step: let me click on the nodes.
[Scientific American via @hmason]
As the Eurozone crisis develops, the BBC News has a look at what country owes what to whom:
Europe is struggling to find a way out of the eurozone crisis amid mounting debts, stalling growth and widespread market jitters. After Greece, Ireland, and Portugal were forced to seek bail-outs, Italy - approaching an unaffordable cost of borrowing - has been the latest focus of concern.
But, with global financial systems so interconnected, this is not just a eurozone problem and the repercussions extend beyond its borders.
Simply click on a country, whose arc length represents how much they owe, and arrows show debt.
[BBC News | Thanks, Eugene]
If you don't watch the candidate debates — and let's face it, that's just about everyone — you pretty much miss everything, except for stuff like Rick Perry forgetting agency names. Politilines, by Periscopic, lets you see what the candidates talked about each night.
The left column lists top issues, the middle shows words used, and the right column shows candidates. Roll over any word or name to see who talked about what or what was talked about by whom.
The method:
We collected transcripts from the American Presidency Project at UCSB, categorized them by hand, then ranked lemmatized word-phrases (or n-grams) by their frequency of use. Word-phrases can be made of up to five words. Our ranking agorithm accounts for things such as exclusive word-phrases - meaning, it won't count "United States" twice if it's used in a higher n-gram such as "President of the United States."
While still in beta, the mini-app is responsive and easy to use. The next challenge, I think, is to really show what everyone talked about. For example, click on education and you see Newt Gingrich, Ron Paul, and Rick Perry brought those up. Then roll over the names to see the words each candidate used related to that topic. You get some sense of content, but it's still hard to decipher what each actually said about education.
Posts and links get shared over and over again, but we usually don't know how. We get counts, but who shares what and how far do does a link reach? Google+ Ripples gives you a peak into the process. A link or status is posted, and like when a pebble is dropped in a pond, a pattern forms outwards.
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In 1937, mathematician Lothar Collatz proposed that given the following algorithm, you will always end at the number 1:
Developer Jason Davies puts it into reverse and shows all the numbers that fall within an orbit length of 18 or less. Press play, and watch the graph grow. Mostly a fun animation for nerds like me.
When you walk the beer aisle at the grocery store, there are lots of different brands and types, so it can be easy to think that all of those beverages come from different companies. Maybe you felt like supporting the little guy by buying that beer that looks like it came from a smaller brewery; however, you just might be buying from one of the big guys. In a follow-up to the soda structure map, Phil Howard and Ginger Ogilvie map the structure of the top 13 beer companies.
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Mike Bostock visualizes mobile patent lawsuits, improving on a graphic from Thomson Reuters that wasn't so good. Dashed lines are resolved suits and green ones are licenses to the company.
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Hundreds of thousands of people immigrate every year, with some countries seeing higher rates than others. To compare and to gain a better sense of the number of people moving around, Carlo Zapponi created peoplemovin.
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Sarah Kessler and Nick Sigler examine the interconnectedness between major tech companies. I think this might be the beginnings of a tech version of Six Degrees of Kevin Bacon.
There are lots of people on Twitter who talk visualization. Moritz Stefaner had some fun with Gephi for a view of a whole lot of those people. He calls it the Vizosphere.
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Digital artist Jer Thorp discusses the algorithm and tool used to arrange 9/11 victims' names based on who they were with when they died. The process started with the collection of data.
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Jeffrey Winter tests a hunch about links leading to philosophy on Wikipedia:
There was an idea floating around that continuously following the first link of any Wikipedia article will eventually lead to "Philosophy." This sounded like a reasonable assertion, one that makes a certain amount of sense in retrospect: any description of something will typically use more general terms. Following that idea will eventually lead… somewhere.
Winter's curiosity led to this simple mashup. Type in some terms in the search bar and see where those topics lead to. Lo and behold, they all reach philosophy somehow. The above was my own search for economy, poop, science, Forrest Gump, hamburger, and Chicago. Philosophy: the Kevin Bacon of Wikipedia.
The IBM Visual Communication Lab published their first of what I hope many sketches exploring topics covered by The New York Times and its authors called NYTimes Writes, by Irene Ros. Start with a search term, and the tool will fetch related articles from the past 30 days. You'll get something that looks like the above, which is what I got when i searched for "data."
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FlowingData explores how designers, statisticians, and computer scientists are using data to understand ourselves better — mainly through data visualization. More...
Where are the biggest box office movies (not) streaming?
Find out what percent you are in
High-resolution maps of science
Backbone of the flavor network
Cinemetrics creates a visual fingerprint for movies
Vehicles involved in fatal crashes
World subway paths at scale
Visualize This