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. The new ads for Facebook Home are propaganda clips. Transforming vice into virtue, they’re social engineering spectacles that use aesthetic tricks to disguise the profound ethical issues at stake.
    Facebook Home Propaganda Makes Selfishness Contagious | Wired Opinion | Wired.com

    Another good line: “My argument is that some convictions deserve to be innovation proof. “
    3. 3 weeks ago  Notes (1)
  3. Social media are an important part of the lives of hundreds of millions of users around the world. If you are one of them, maintaining perspective is important. Do not let narcissists set your standards. You may be lagging far behind in the social media rat race because your NPI (Narcissistic Personality Inventory) score is not high enough. The reason you may not have thousands of followers on Twitter and friends on Facebook is because you are normal. Normalcy is a benchmark any narcissist should aspire to achieve.

    The Internet ‘Narcissism Epidemic’ - Bill Davidow - The Atlantic

    Even if you don’t agree with Davidow, this piece contains a nice round-up of links to research on how social media and internet activity can affect personality and offline perspective.

    4. 1 month ago  Notes (1)
  4. 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. 

    5. 1 month ago  Notes (2)
  5. (via Twitter users forming tribes with own language, tweet analysis shows | News | guardian.co.uk) Very intriguing way of grouping Twitter users based on word usage. Researchers think new ways of engaging communities can come out of this sort of breakdown. Worth a look at how the groups are split up. Data sheet embedded in article, also available for download.

    (via Twitter users forming tribes with own language, tweet analysis shows | News | guardian.co.uk)

    Very intriguing way of grouping Twitter users based on word usage. Researchers think new ways of engaging communities can come out of this sort of breakdown. Worth a look at how the groups are split up. Data sheet embedded in article, also available for download.

    6. 2 months ago  Notes (30)