Tag: big data

  • Charge up data reach with smart UX

    Charge up data reach with smart UX

    data_meeting

    Last week I participated in a data and gov tech roundtable hosted by Nick Sinai at the Shorenstein Center at Harvard Kennedy School. Nick brought together an all-star panel with Lynn Overmann, Todd Park, Aneesh Chopra, and newly-named U.S. Chief Data Scientist D.J. Patil. Entrepreneurs, academics, and officials exchanged ideas on the challenges of collecting, structuring, and delivering meaningful open data.

    Patil led off with his (Day 5!) understanding of his new role, which — I was heartened to hear — included a mention of the importance of user experience. Back in the late 1990s, websites were created on the premise of “Build it and they will come.” Early release of data sets suffers from a similar problem — it’s hard to attract a wide range of users with only machine readable formats. Government officials invested in sharing data are realizing that a better approach to user experience is needed to get the data in the hands of more users. Ideally, an infrastructure will be created to meet this need, and it’s not yet clear how much public-private partnerships will (or should) play that role.

    As more government data is released (new datasets were announced today from the Department of Veterans Affairs, the Department of Labor and the Environmental Protection Agency), there is greater potential value for researchers and journalists. While improved data literacy is coming, the challenge of user experience remains critical to solve to reach wider audiences.

  • Friday 5 — 12.12.2014

    Friday 5 — 12.12.2014

    Facebook mobile

    1. Facebook is surging ahead on mobile revenue as well as mobile market share. Facebook now accounts for about one-fifth of all data used on mobile phones, and owns four out of the top ten apps in the Apple iOS store and Google Play. More over at Quartz.
    2. Dark social is a term introduced by Alexis Madrigal two years ago to define the kinds of social sharing  (email, instant messaging, texting, etc.) that were not clearly attributed in analytics. Here he updates his hypothesis of dark social with the discovery that a good deal of this traffic is now trackable and attributable to Facebook sharing on mobile devices — which may be so prevalent now that it is eroding other ways of sharing.
    3. Does the internet help you learn new things? 87% of Americans believe that it does. Also interesting: 72% say that the internet allows them to share their ideas and creations with others, a significant rise since 2006. This increase aligns with the mass adoption of social networking tools, and the ease of instantaneous publishing of text, images, and video through these platforms.
    4. Whether you are paralyzed by choice in music discovery, or merely lazy enough to outsource all your listening habits to cooler friends, Spotify has got you covered. Try out “Top Tracks in Your Network” for a personalized, updated playlist based on what friends you follow are listening to.
    5. Machine intelligence, defined here as what becomes possible as computers develop and scale abilities previously limited to humans, is poised to transform industries and create entirely new ones. Here’s a great chart of the landscape, and enumeration of relevant trends and opportunities.

    Weekend fun: Deadspin may call my favorite team a “Godless Abomination,” but all basketball fans will enjoy Buckets, a quantitative approach to viewing shooting across all NBA teams and players.

    buckets

     

    Every Friday, find five, highly subjective pointers to compelling technologies, emerging trends, and interesting ideas that affect how we live and work digitally. Try out the Friday 5 archive, or sign up for a weekly email.

  • Friday 5 — 4.18.2014

    Friday 5 — 4.18.2014

    1. carousel app Now that we’re all shooting more photos and videos than ever before, Dropbox is hell bent on storing them for you. Dropbox knows there’s a high switching cost for moving all your personal stuff (hassle, trust) so they’re making it easy and appealing to store and share, particularly via mobile. And yesterday Dropbox purchased iOS photo app Loom to continue the offensive.
    2. This week, Twitter took a page out of Facebook’s monetization playbook by adopting app install ads. With a heavily mobile user base, Twitter provides an appealing audience for app creators looking for new users. Here’s hoping this proven ad revenue model shores up Twitter’s languishing stock price.
    3. Hunter Walk illustrates how context matters when serving up recommendations for end users. When YouTube recommended videos to users, the interface explicitly told them why: e.g., “because you watched these puppy videos, we’re showing you this kitten.” As a result, users were less likely ignore the recommendations — and consumed more video.
    4. But what if you don’t want your online behavior tracked, for relevant video recommendations or anything else? The Atlantic cites research from Zeynep Tufekci on emerging user behaviors, from passive-aggressive subtweeting to active hatelinking, that regular people are adopting to remain invisible to the algorithms that track online behavior.
    5. Also filed under “what your social networks now know about you,” Facebook has launched Nearby Friends, a way for you to find out who’s close by. The technology is based on Glancee, a startup Facebook acquired back in 2012. Needless to say, early messaging is all about user control and privacy settings.

    Weekend fun: Done right, Vine videos are a glorious, six-second art form. Here are this year’s winners from the Tribeca Film Festival, with my favorite Wrap Dancer winning the animation category.

    Every Friday, find five, highly subjective links about compelling technologies, emerging trends, and interesting ideas that affect how we live and work digitally.

  • Try it: Visualize search worldwide

    US search terms trending

    Add another curiously mesmerizing big data visualization to your procrastination list. This colorful visualization serves up a (presumably filtered for a G rating) constantly-updating view of all the Google search terms people in the U.S. are entering in near real-time. For fun, toggle over to see search terms in ten other countries, including Australia, India, and Russia.

    Feature request: a customized version for brands to visualize the terms most frequently associated with the brands, like “Arsenal + Wenger” or “Harvard + financial aid.” There are other ways to discover those terms, but would be terrific to visualize them out of the box for a presentation on brand associations.

  • Friday 5 – 05.24.2013

    Every Friday, find five quick links about compelling technologies, emerging trends, and interesting ideas. Source: the internet.

    1. There’s a new Pew Internet/Berkman Center report on teens and privacy. The report confirms that sharing on social is up overall; more teens are on Twitter; and enthusiasm for Facebook and its drama may be waning. 
    2. Those mobile-savvy teens eschewing Facebook in favor of Tumblr now find themselves on Yahoo, as the 1.1B purchase was finalized this week. With a mixed track record for acquisitions, can Yahoo keep its promise not to screw it up?
    3. Storify and Typekit team up to help brands customize their stories. As the world becomes more real-time and social, Storify is a canny curatorial end run against enterprise CMS; offering better customization options for paying customers is a smart move.
    4. Over 2 million Oklahoma tornado tweets have been automatically processed. As citizens have solidified their presence as social media news sources in recent events including Oklahoma, Boston, and London, automating analysis using algorithms will be essential to separate news from noise.
    5. Finally, NPR reports from the future on the use of bots in therapeutic settings. As we begin to narrow what falls into the uncanny valley of creepy, human-like interaction, I predict these kinds of bots will turn up in a wide range of interactions from caregiving to news reading.
  • The inevitability of big data hacks

    Geeks often talk about “layer 8.” When an IT operator sighs resignedly that it’s a layer 8 problem, she means it’s a human’s fault. It’s where humanity’s rubber meets technology’s road. And big data is interesting precisely because it’s the layer 8 protocol. It’s got great power, demands great responsibility, and portends great risk unless we do it right. And just like the layers beneath it, it’s going to get good, then bad, then stable.

     

    Other layers of the protocol stack have come under assault by spammers, hackers, and activists. There’s no reason to think layer 8 won’t as well. And just as hackers find a clever exploit to intercept and spike an SSL session, or trick an app server into running arbitrary code, so they’ll find an exploit for big data.

    — Alistair Croll in Stacks get hacked: The inevitable rise of data warfare. Croll points out that with each new technology, there’s an evolution from good to bad to stable — and we should expect that same trajectory with big data.

    Interesting to think about how large-scale exploits to corrupt the data about everything from public opinion on an issue to real estate attributes could have massive effects on decisions and markets.

  • Unpacking the algorithms behind online experiences

    Relinquishing human free will to the machines generally gets a bad rap. In the media, all kinds of scientists are nefarious in their data-driven ways — even well-intentioned science yields Frankenstein’s monster far more often than the reasonable paleontologist in Jurassic Park. The Terminator franchise in the 1980s was among the first to introduce the concept of the Singularity to mass media — what happens to humans when their systems become self aware? — with predictable dire results. (According to futurist Ray Kurzweil the Singularity is now only 17 years away — so look busy.)

    And yet in our online lives, we cede more and more to algorithms and machine learning. Eli Pariser highlighted the risks of our collective inattention to the use of algorithms in his 2011 The Filter Bubble. He pointed out that applications like Facebook show us only a curated subset of our friends, just as Google in 2009 began to filter our searches for us — even when we’re logged out. Apart from intermittent outrage in front page stories (“Target knew my teen daughter was pregnant before I did!”), we don’t often question the convenience that all these behaviorally-fueled algorithms offer us. We may cringe at ads that re-target us around the web, but as long as we use the conveniently-timed coupons offered to us, we are encouraging rather than curtailing that behavior.

    Recently I’ve been reading more about Echonest, the technology that sits behind music discovery applications like Spotify and Vevo. In many ways this feels like a highest and best use of an algorithm. Who has time to manually curate playlists for everything from a workout to a night out? The algorithms go further to infer musical compatibility among friends, and have even taken a swing at how musical tastes align with political leanings – handy for those throwing national conventions or debate watch parties. The risks seem low compared to algorithmically-led access to one’s friends, but of course there’s the opportunity to skew music discovery to industry-backed new artists à la Clear Channel. While some analysts are bullish on Pandora’s music genome approach (similar to Art.sy’s attempt to map the art genome – h/t Cesar Brea), other investors are betting heavily on Echonest. A few weeks ago Echonest made public their Discovery playlist, which updates each week with emerging music from around the globe. Algorithms find out what people are listening to and taking about, and offer a great way to find new music around the world in a ways most humans can’t scale — well before it’s piped to you in the mall.

    In the end, it’s all the same acknowledgement of the impossibility of the big data in our lives. It requires admitting the information overload is too great, and a degree of outsourcing selection to the machines. So maybe algorithms are less creepy when we know they’re out there working for us, and when they are finding needles from the broadest possible haystack — music we might like, seeing friends through the lens of musical compatibility — rather than surreptitiously defining the status updates we get to see.

  • Welcome to the age of big data

    It’s a revolution,” says Gary King, director of Harvard’s Institute for Quantitative Social Science. “We’re really just getting under way. But the march of quantification, made possible by enormous new sources of data, will sweep through academia, business and government. There is no area that is going to be untouched.