Infographic Of The Day: Is "The 1%" Inevitable, Given How Networks Work? | Co.Design The viral protest meme known as "Occupy Wall Street" is still going strong, and according to some provocative research to be published in PLoS One, it may never have reason to run out of steam. Why? Because "the 1%"--#OWS-speak for the tiny subgroup of wealthy interests that exerts outsize influence over "the 99%" comprising the rest of us--may be a mathematically inevitable consequence of the way networks self-organize. The paper, entitled "The network of global corporate control", is an attempt by complex systems theorists at the Swiss Federal Institute of Technology in Zurich to "go beyond ideology to empirically identify such a network of power," according to New Scientist. The study and infographic have generated lots of press and intense debate about the researchers’ methodology and assumptions (for example, that stock ownership is a proxy for direct influence/control). [Via New Scientist]
Chart Porn Promising difficulties At the recent VisWeek conference, Jessica Hullman and her coauthors presented ”Benefitting Infovis with Visual Difficulties (pdf)”, a paper that suggests that the charts which are read almost effortlessly are not necessarily the ones that readers understand or remember best. To answer that claim, Stephen Few wrote a rather harsh critique of this paper (pdf). As I read this I felt the original paper was not always fairly represented, but more importantly, that the views develop by both parties are not at all inreconcilable. Let me explain. What is cognitive efficiency, or “say it with bar charts” For quite some time, we were told that to better communicate with data, we had to make visuals as clear as possible. The more complicated way of saying that is talking of “cognitive efficiency”. Various charts based on the same data points. For instance: bar charts are easier to process than pie charts, because it’s easier for the human eye to compare lengths than angles. Fair enough! Agreed!
chartsnthings 19 Sketches of Quarterback Timelines On Sunday Eli Manning started his 150th consecutive game for the Giants, the highest active streak in the NFL and the third-longest streak in NFL history. (One of the other two people above him is his brother, Peyton.) The graphics department published an interactive graphic that put Eli’s streak in the context of about 2,000 streaks from about 500 pro quarterbacks. The graphic lets you explore the qbs and search for any quarterback or explore a team to go down memory lane for your team. It’s not particularly important news, but the data provided by pro-football-reference is incredibly detailed and the concept lended itself to a variety of sketches. A couple bar charts in R. And percent of games started (the people are 100% are players like Andrew Luck or RGIII who just haven’t played a lot of seasons.) Ported to a browser, just using total starts: And share of total possible starts …or all the way back to 1970
Treasure hunting for the whole family - Chatham Daily News - Ontario, CA Ever heard of Geocaching? Neither did I until Friday. Geocaching is a real-world outdoor treasure-hunting game. Then again, the booty won't likely knock your socks off. But kids like it. I took Friday off to spend the P.A. day with my daughter and her cousin. After three days of rain, it was nice to get outdoors Friday, even under overcast skies, and with that cool wind out of the northwest. Uncle Steven pulled out his iPhone and found the nearest stash - about half a mile to the south. Off we went, on foot through residential subdivisions. After snaking through The Maples, we closed in on the paths beside the drain (I hate calling creeks such things as "drains"). Despite the fact our first foray ended in failure, our spirits remained undaunted. No, there's no Geocache there, but there's a hill and playground equipment, treasure indeed for two young kids. We eventually returned home, gave the kids a brief rest and tried again as the day began to give way to night. "I cleaned it off." Hmm.
TAGSExplorer: Interactively visualising Twitter conversations archived from a Google Spreadsheet MASHe Graphs can be a powerful way to represent relationships between data, but they are also a very abstract concept, which means that they run the danger of meaning something only to the creator of the graph. Often, simply showing the structure of the data says very little about what it actually means, even though it’s a perfectly accurate means of representing the data. Everything looks like a graph, but almost nothing should ever be drawn as one. Ben Fry in ‘Visualizing Data’ I got that quote from Dan Brickley’s post Linked Literature, Linked TV – Everything Looks like a Graph and like Dan I think Ben Fry has it spot on. When I started following Tony’s work on network analysis (here’s a starting point of posts), my immediate response was ‘Where’s Wally?’ As I start my exploration of tools like NodeXL it's very clear that being able to filter, probe and wander through the data provides far more insights to what’s going on. But what does this graph actually mean? *** TAGSExplorer ***