1. (via Stephen Wolfram Blog : Data Science of the Facebook World)All of this post is very interesting, but this visualization of the author’s 15-year-old daughter’s Facebook network and the ones that follow caught my attention the most. It illustrates, to some extent, where the source of her connections on the medium come from. The analysis that follows is worth a look.It’s of course logical that we have different clusters of friends on social networks, probably particularly so in the case of Facebook. It’s neat here, however, that data may suggest there’s a most typical number of clusters that make up the majority of an individual’s network: three.Years ago, I also went to one-time events like summer camps, and I am still friends with most of those folks on Facebook. I’ve probably neglected the size of those resulting clusters in my own network. But odds are that years later — after a handful of schools, jobs and one-time events like conferences — the show choir camp I attended in high school doesn’t make up one of my major three clusters. But I’m willing to bet a cluster I don’t think about or engage with in real life all the time definitely does.(And who knows, maybe it actually is that show choir group. For someone who is involved pretty heavily in journalism, I do see a lot of news in my stream that deals not with great free tools for online storytelling, but instead, something like who won grand champions at a random competition in Iowa.) It’s interesting, in general, to think about what those three(ish) clusters may be for every individual user on the platform. There is some level of filter bubble and we do see content from people similar to us in a place like Facebook. But perhaps it’s worth opening up and examining which “people like us” we see most. Or, at the very least, determining the ones that have a shot, sticking around and gaining influence in our network because of their sheer size.

    (via Stephen Wolfram Blog : Data Science of the Facebook World)

    All of this post is very interesting, but this visualization of the author’s 15-year-old daughter’s Facebook network and the ones that follow caught my attention the most. It illustrates, to some extent, where the source of her connections on the medium come from. The analysis that follows is worth a look.

    It’s of course logical that we have different clusters of friends on social networks, probably particularly so in the case of Facebook. It’s neat here, however, that data may suggest there’s a most typical number of clusters that make up the majority of an individual’s network: three.

    Years ago, I also went to one-time events like summer camps, and I am still friends with most of those folks on Facebook. I’ve probably neglected the size of those resulting clusters in my own network. But odds are that years later — after a handful of schools, jobs and one-time events like conferences — the show choir camp I attended in high school doesn’t make up one of my major three clusters. But I’m willing to bet a cluster I don’t think about or engage with in real life all the time definitely does.

    (And who knows, maybe it actually is that show choir group. For someone who is involved pretty heavily in journalism, I do see a lot of news in my stream that deals not with great free tools for online storytelling, but instead, something like who won grand champions at a random competition in Iowa.)

    It’s interesting, in general, to think about what those three(ish) clusters may be for every individual user on the platform. There is some level of filter bubble and we do see content from people similar to us in a place like Facebook. But perhaps it’s worth opening up and examining which “people like us” we see most. Or, at the very least, determining the ones that have a shot, sticking around and gaining influence in our network because of their sheer size.

    2. 1 week ago  Notes (1)

  2. Startup Sherpa Bets Its Predictive Smartphone Assistant Can Best Google Now | MIT Technology Review

    Predictive News?

    The more I read about Google Now and Sherpa, the more I can’t help but think about how the same predictive intelligence for news apps would be so effective. If done right, it could fill many “jobs to be done.”

    A smart, predictive news app would be a step above my “OpenMoment” idea/desire, which outlines a mobile app that sorts news by real-life context. Rather than have to select “morning commute” and filter news that fits your preferences for a long Metro ride — like I thought by itself would be pretty cool — smart technology could use your location and time data to automatically suggest news material your most likely to read and enjoy.

    It could do that for a commute, a lunch line, the “lean back” hours of the evening, etc., always suggesting the most appropriate content for each context. I’d sign up right away. It’d save me some time and potentially lend itself to discovery I may have missed out on. 

    I know some people are experimenting with this realm of mobile location + news (Kon*Fab comes to mind). Perhaps experimentation will become easier as Google Now and Sherpa get going and we’ll be able to see some news outlets get into the game, too.

    Location and time data spliced together could offer pathways to answering big relevancy questions in media (in the information overload we all recognize, how do we serve stories or information readers will want to see). And I’m sure there are a hefty plenty of possibilities for targeted advertising based on both location and time of day… 

    3. 1 month ago  Notes (0)
  3. If you don’t regularly exercise your ability to connect face to face, you’ll eventually find yourself lacking some of the basic biological capacity to do so.

    Your Phone vs. Your Heart - NYTimes.com

    Research soon to be published in Psychological Science suggests that individual actions and habits regarding how we relate to each other and the ways in which we use technology can leave lasting fingerprints on health and empathic skills.

    Looks like it’d be particularly important for children and adult interaction (as the article mentions, instances “like [parents] texting while breast-feeding or otherwise paying more attention to their phone than their child”).

    This important to remember for individuals, broadly. It’s additionally worth consideration for designing for any new technology and communication. 

    4. 1 month ago  Notes (2)
  4. (via Friends and Family – Important Drivers of News | State of the Media) Word-of-mouth still motivates a large amount of news discovery. Seventy-two percent who get news from friends or family received that information via spoken word-of-mouth (in person or phone). Of those who learn of news this way, nearly two-thirds “often” or “very often” seek out news stories online later.The breakdowns vary a little bit by age, as to be expected: 23 percent of those age 18 to 29-years-old get news from family or friends via social media. Seventy percent in this bracket still say word-of-mouth, however.This of course doesn’t mean that those who get news via word-of-mouth don’t also read engage news elsewhere on their own. But it does make you think about 1) what inspires people to share something IRL, and 2) the importance of SEO and other search functionality. The stats are at least worth a look, as is the rest of this year’s Pew Excellence in Journalism State of the News Media report. 

    (via Friends and Family – Important Drivers of News | State of the Media)

    Word-of-mouth still motivates a large amount of news discovery. Seventy-two percent who get news from friends or family received that information via spoken word-of-mouth (in person or phone). Of those who learn of news this way, nearly two-thirds “often” or “very often” seek out news stories online later.

    The breakdowns vary a little bit by age, as to be expected: 23 percent of those age 18 to 29-years-old get news from family or friends via social media. Seventy percent in this bracket still say word-of-mouth, however.

    This of course doesn’t mean that those who get news via word-of-mouth don’t also read engage news elsewhere on their own. But it does make you think about 1) what inspires people to share something IRL, and 2) the importance of SEO and other search functionality.

    The stats are at least worth a look, as is the rest of this year’s Pew Excellence in Journalism State of the News Media report. 

    5. 2 months ago  Notes (1)
  5. (via Photo by todayshow • Instagram) A bit different, kind of like the Obama inaugurations. EDIT: But since this started circling, we’ve also learned that it’s not quite a fair comparison: the top image appears to be from John Paul II’s funeral procession, not the announcement of a new pope.  A compelling storyline about tech’s growing pervasiveness, but a little too apples and oranges. Moods of events — not just years — also affect human behavior with tech. (That said, some people have recently livetweeted funerals.)(In any case,the person in the bottom right corner of the photo of the 2005 image still reminds me of this).

    (via Photo by todayshow • Instagram)

    A bit different, kind of like the Obama inaugurations. EDIT: But since this started circling, we’ve also learned that it’s not quite a fair comparison: the top image appears to be from John Paul II’s funeral procession, not the announcement of a new pope. 

    A compelling storyline about tech’s growing pervasiveness, but a little too apples and oranges. Moods of events — not just years — also affect human behavior with tech. (That said, some people have recently livetweeted funerals.)

    (In any case,the person in the bottom right corner of the photo of the 2005 image still reminds me of this).

    6. 2 months ago  Notes (7)