Self-Described Mac vs. PC People infographic Profile of a Self-Described Mac Person vs. PC Person is a fun infographic looking at personality and preference differences. Based on 388,315 survey respondents from Hunch.com, it illustrates topics like who throws parties, math aptitude, taste in art, cocktail drinks of choice and would they ride a Vespa or a Harley. Our latest data project was to analyze how self-described Mac and PC people are different. The infographic below, designed by the talented folks at Column Five Media, breaks it down.Back in ye olden days of Hunch — November 2009 — we explored the differences in personality, aesthetic tastes, and media preferences between Mac and PC users. Since then, the Hunch user base and question pool have grown many times over. From a research standpoint, even though the number of respondents is high, these are voluntary survey participants that haven’t gone through a screening process. Very funny, and a great job by the design team at Column Five Media!
Color as Data: Visualizing Color Composition by Maria Popova Abstracting glossy magazines, or what pie charts have to do with the Mona Lisa. We love data visualization and color. Computational artist Mario Klingemann, a.k.a. The pie charts represent the distribution of dominant colors within a circle area. Designer Shahee Ilyas‘ amusingly minimalist deconstruction of country flags by color composition is an absolute treat. Besides the playful irreverence, the project reveals some curious patterns of color choice, raising even more curious questions about color symbolism. Data viz superheroes Martin Wattenberg and Fernanda Viegas have taken their visualization magic to the world of fashion photography. To create the images in luscious, we began with a series of magazine advertisements for luxury brands. Brain Pickings has a free weekly newsletter and people say it’s cool. Share on Tumblr
Meet the Data Brains Behind the Rise of Facebook | Wired Enterprise Facebook’s Jay Parikh. Photo: Ariel Zambelich/Wired Jay Parikh sits at a desk inside Building 16 at Facebook’s headquarters in Menlo Park, California, and his administrative assistant, Genie Samuel, sits next to him. Parikh is Facebook’s vice president of infrastructure engineering. The trouble is that the Facebook infrastructure now spans four data centers in four separate parts of the world, tens of thousands of computer servers, and more software tools than you could list without taking a deep breath in the middle of it all. But that’s why Parikh and his team build tools like Scuba. “It gives us this very dynamic view into how our infrastructure is doing — how our servers are doing, how our network is doing, how the different software systems are interacting,” Parikh says. In the nine years since Mark Zuckerberg launched Facebook out of his Harvard dorm room — Monday marks the anniversary of the service — it has evolved into more than just the world’s most popular social network.
Startup Lessons From The Ink-Stained Trenches Startup founders and news reporters have more in common than being stereotypically broke. Before the music and airplanes and space ships, billionaire tycoon Richard Branson’s first business was a magazine, of which Branson was editor-in-chief. Before launching the now $2.5 billion fashion company, Banana Republic’s founder was a journalist. Where the skills of business and journalism overlap, entrepreneurship is often found. Columbia Journalism School, founded by Joseph Pulitzer in 1912, lists 40 startups launched by its students in the last five years, including AllThingsD, Spot.us (a news-focused progenitor to Kickstarter), and Vayable. "Journalists hone... reporting muscles that are hugely helpful for entrepreneurship,” says Jeremy Caplan, Director of Education at CUNY’s Center for Entrepreneurial Journalism. I’ve made surprising use of my journalism training in running my own startup, Contently. Here are cues every entrepreneur should take from journalists: Ask good questions.
10 Essential Fiscal Charts FORM+CODE: Eye and Brain Candy for the Digital Age by Maria Popova Computational aesthetics, or what typography has to do with Yoko Ono and Richard Dawkins. Yes, we’re on a data visualization spree this week, but today’s spotlight taps into an even more niche obsession: data viz book candy. This season, Princeton Architectural Press, curator of the smart and visually gripping, brings us FORM+CODE — an ambitious, in-depth look at the use of software across art, design and illustration for a wide spectrum of creative disciplines, from data visualization to generative art to motion typography. The nature of form in the digital age is trapped in the invisible realm of code. Elegant and eloquent, compelling yet digestible, the tome — dubbed “a guide to computational aesthetics” — offers a fine piece of eye-and-brain stimulation for the age of digital creativity. Thanks, Julia Brain Pickings has a free weekly newsletter and people say it’s cool. Share on Tumblr
Wonga, Lenddo, Lendup: Big data and social-networking banking Photo by Johannes Simon/Getty Images The buzzword tsunami that is “big data"—a handy way of describing our vastly improved ability to collect and analyze humongous data sets—has dwarfed “frictionless sharing” and “cloud computing” combined. As befits Silicon Valley, “big data” is mostly big hype, but there is one possibility with genuine potential: that it might one day bring loans—and credit histories—to millions of people who currently lack access to them. But what price, in terms of privacy and free will (not to mention the exorbitant interest rates), will these new borrowers have to pay? In the not so distant past, the lack of good and reliable data about applicants with no credit history left banks little choice but to lump them together as high-risk bets. Thanks to the proliferation of social media and smart devices, Silicon Valley is awash with data. Similarly, the U.S. Social media is just the tip of the iceberg. Those without smartphones or Twitter accounts need not despair.
The problem with "global warming" We are facing what might be the greatest threat ever to the future of mankind. And yet no one is marching in the streets, the outrage is largely intellectual and action is slow. (If you want to argue about the science, please visit the link above, this is a post about the marketing!) Is the lack of outrage because of the population's decision that this is bad science or perhaps a thoughtful reading of the existing data? Actually, the vast majority of the population hasn't even thought about the issue. The muted reaction to our impending disaster comes down to two things: 1. the name. Global is good.Warm is good.Even greenhouses are good places. How can "global warming" be bad? I'm not being facetious. 2. the pace and the images. One degree every few years doesn't make good TV. Lady Bird Johnson understood this when she invested her efforts into a campaign against litter and pollution. Doesn't matter what you market.
Applying Sentiment Analysis to the Bible « OpenBible.info Blog This visualization explores the ups and downs of the Bible narrative, using sentiment analysis to quantify when positive and negative events are happening: Full size download (.png, 4000×4000 pixels). Things start off well with creation, turn negative with Job and the patriarchs, improve again with Moses, dip with the period of the judges, recover with David, and have a mixed record (especially negative when Samaria is around) during the monarchy. The exilic period isn’t as negative as you might expect, nor the return period as positive. Methodology Sentiment analysis involves algorithmically determining if a piece of text is positive (“I like cheese”) or negative (“I hate cheese”). I ran the Viralheat Sentiment API over several Bible translations to produce a composite sentiment average for each verse. The visualization takes a moving average of the data to provide a coherent story; the raw data is more jittery. Update October 10, 2011 Full size download (.png, 2680×4000 pixels).
7 Essential Books on Data Visualization & Computational Art by Maria Popova What 12 million human emotions have to do with civilian air traffic and the order of the universe. I’ve spent the past week being consistently blown away at the EyeO Festival of data visualization and computational arts, organized by my friend Jer Thorp, New York Times data artist in residence, and Dave Schroeder of Flashbelt fame. Processing, the open-source programming language and integrated development environment invented by Casey Reas and Ben Fry in 2001, is easily the most fundamental framework underpinning the majority of today’s advanced data visualization projects. Recommended by: Casey Reas Since 2005, (a longtime Brain Pickings favorite) have been algorithmically scrobbling the social web to capture occurrences of the phrases “I feel” and “I am feeling” harvesting human sentiment around them by recording the full context in which the phrase occurs. Reviewed in full here. Recommended by: Jer Thorp Recommended by: Moritz Stefaner Recommended by: Wes Grubbs
Top Five Big Data Trends For 2013 I can say this with absolute certainty: The holiday season will underscore the impact of big data on retail. Already, the early sales results begin to tell the story, pointing towards data-rich e-commerce as the big winner. From comScore: Black Friday alone saw $1.042 billion in online sales. That’s the first time online spending on the day after Thanksgiving has crested $1 billion, and it’s also a respectable 26 percent increase versus Black Friday 2011. Of course, now the question at the top of the agenda is this: Where will we go from here? Looking ahead, here are the big data trends I’m expecting in the New Year: More and different use cases. Enhanced collaboration and integration. Related Resources from B2C» Free Webcast: Four Ways To Improve Your Content Marketing Maturity Better insights. Amped up mobile wars. Increased scrutiny of privacy issues. That’s a brief synopsis of the major big data trends I see on the horizon.