• The Current State of Social Data

    June 16, 2009  |  Social Data Analysis

    Check out my guest post on The Guardian's Data Blog on the current state of social data applications. There are what seems like a ton of them but none of them have really taken off (yet).

    While the post is more of an overview of what's available, I'd like to start a little discussion here on why these data apps haven't gained more popularlity. There always seems be a lot of buzz around launch time, but then it fizzles.

    Are people just not interested in interacting with data or do we need to approach the whole social data puzzle from a different angle?

  • 3 Applications that Tap Into the Wisdom of Crowds

    September 30, 2008  |  Social Data Analysis

    crowd

    James Surowiecki writes in The Wisdom of Crowds that the group is smarter than the individual (under four conditions). Essentially, the premise is that if you get enough different people to work on a single problem independently, you're going to get as good or better results than that of a small group of experts working together. Think of it as advanced crowdsourcing.

    These three applications tap into the wisdom of crowds. It's clearly election season.
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  • Tap Into the Wisdom of Crowds, Make Money by Predicting Future Events

    February 5, 2008  |  Social Data Analysis

    Predictify LogoPredictify takes James Surowiecki's The Wisdom of Crowds to heart. Surowiecki argues that when certain factors are present (for example, group diversity), then the group is always smarter than the individual. Predictify has turned this "principle" into a money-making platform.
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  • Going Beyond Collaborative Visual Analytics with Statistics

    January 15, 2008  |  Social Data Analysis

    Jeffrey Heer et al. writes in Design Considerations for Collaborative Visual Analytics about a couple of models for social visualization -- information visualization reference model and the sensemaking model. The former is a simpler, more straightforward model starting with raw data -> processed data -> visual structures -> actual visualization; while the latter is a bit more complicated with similar stages but with feedback loops. My main reflections weren't so much with the ideas proposed by the paper. Rather, I'm more interested in what was not mentioned -- not only in this paper but in other social data analysis papers.

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  • Sharing Personal Data to Push Social Data Analysis

    November 19, 2007  |  Social Data Analysis

    I'm staying in a hostel here in Madrid and am currently in the "Internet Room." I'm on my laptop, but there are six desktop computers in front of me, all of which are occupied. Three of the six people have Facebook open plus myself. It's come to the point that Facebook has so many ways to share information, that almost everyone can find some use for it. Is there some way to share data in some similar social way?

    I know there's some data blogging available and a few social data sites, but they don't have the same feel as Facebook. I think the main reason people like Facebook (other than an entertaining way to waste a few hours) is because they personally relate to the information displayed and there's some kind of connection between friends and strangers.
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  • Social Data Analysis by the Swarm

    July 4, 2007  |  Social Data Analysis

    swarm500

    Swarm Theory, by Peter Miller, talks about how some animals, as individuals, aren't smart, but as a group or a swarm, they can do amazing things. The above is a flock of starlings that can change shapes even though no single bird is the leader.

    Can we apply swarm theory to social data analysis? As individuals, we might not be able to hold onto or understand a dataset, but as a group, we can come at a dataset from different perspectives, look at very small parts, and then as an end result -- extract real, worthwhile meaning.

    That's how swarm intelligence works: simple creatures following simple rules, each one acting on local information. No ant sees the big picture. No ant tells any other ant what to do. Some ant species may go about this with more sophistication than others. (Temnothorax albipennis, for example, can rate the quality of a potential nest site using multiple criteria.) But the bottom line, says Iain Couzin, a biologist at Oxford and Princeton Universities, is that no leadership is required. "Even complex behavior may be coordinated by relatively simple interactions," he says.

    It reminds me of that common saying, or maybe it's a quote, about how if you put a bunch of monkeys in a room with typewriters, you'll eventually get the works of Shakespeare via the magic of probability. While the whole monkey thing is a bit far-fetched, swarm theory is certainly worth my attention.

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