Posts Tagged ‘twitter’
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Maybe one day we’ll be daring enough to go back
30th March 11
Posted in Shorty awards
No argument with this image from astronaut Douglas H Wheelock (@Astro-Wheels) winning the Shorty Special Award for Best Real-Time Photo of the Year
The rest of the winners and shortlisted twitterati can be found here.
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The answer to this Quora? No.
10th January 11
Posted in Rants
The question-and-answer site Quora is a big deal. It has some powerful supporters, with early content posted by a diverse group of digerati from Steve Case to Robert Scoble. It’s the talk of the media (see Google Trend of the word Quora). There are weekly articles on how Quora will be bigger than Twitter.
So, I guess it was inevitable that I’d hate it. To clarify, it’s not that I don’t like Quora. It’s that I hate it and want it wiped off the face of the earth. In a missionary effort to reach those few that are yet to form an opinion on this site equivalent of an Uwe Boll movie, I offer the following 3 reasons to resist boarding this bandwagon.
It’s spam.
This site diabolically infects those with the largest spam potential. I guess when a site is launched by the former head of Facebook Connect, it’s inevitable. By launching after Facebook established critical mass and Twitter became a big deal, Quora made a splash in the saturated question-and-answer site category. So, giving people the opportunity to be in the spotlight with their answer to an already-answered question is an ingenious way to drive audience and usage by appealing to ego. And I don’t even mind ego-stroking. I just don’t want to be repeatedly spammed across my various feeds as people whose content I otherwise love and trust fall victim to name-in-lights syndrome. Then again, if I could convince people I invented tape, it might be worth it….
There are dozens of Quoras about what Quora is.
OK, so maybe #Twitter was a trending topic on Twitter the first 6 months. But those conversations were focused primarily on usage and innovation with the platform. The Quora self-referential conversations are literally people scratching their heads looking for value. There’s no better sign that the emperor has no clothes people. But until we admit it, we’ll just keep tweeting how awesome he looks in that special toga (author’s note: this has nothing to do with how awesome I think the hashtag #emperorsclothes would be, promise).
Quora is attempting to differentiate itself via answer quality.
This is defended through its use of Facebook Connect (real people!) and an interest graph (curated topics!). Here’s the thing about quality: it’s inversely related to scale on the web. Generally, users or an algorithm are required to remove the noise. Last I looked, countless services already do this. They go by ticker symbols like GOOG, have David Fincher movies made about them, or add a new user every second (most of whom request a professional recommendation after a single meeting together).
So, let’s sit this Quora thing out. We were able to resist Google Wave and Ping. Let’s make it three in a row that we tried and let pass quietly. This isn’t to say I don’t respect the effort or experimentation of any company trying something new (Google & Apple are incredible at innovation investment). In Quora’s case, I just think if it ain’t broke, don’t fix it via my newsfeed.
Now world, if you’re not on board, pretty please give me a heads-up that I’m taking on a lost cause.
Then I can start a new Quora-related Quora: “How can I get a job at Quora?”
{Update: I’ve agreed to write a follow-up post to either eat my words or discuss what I got right after some, ahem, encouragement from readers. So keep an eye out!}
{Update #2: We asked Leslie Barry to elaborate on his comment below and he’s posted a rebuttal, explaining the unique value of Quora I’ve neglected in the post above.}
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Mapping Twitter Part 2: The Tweet-o-Meter
10th March 10
Came across this today. Tweet-o-Meter (link) is the beta version of a platform created by University College London’s Centre for Advanced Spatial Analysis. The Tweet-o-Meter supposedly updates every ten seconds (not sure it does quite do that right now), showing the number of tweets in each city per minute. The ambition is to log and analyze all geo-located tweets in these major cities. Once logged, they will be used to show Twitter activity over time and space. Various kinds of maps will be the main output. I imagine a variety of delicious visualizations will be forthcoming.
We are possibly attracted partly by the simple analogue-feel, dial-based interface. But we’re also struck by yet another work-in-progress attempt to bring life to the data spawned by Twitter (see also Getting to Know Your Twitter Followers & Why that Matters from earlier this week).
Tweet-o-Meter is part of a broader project called NeISS (National e-Infrastructure for Social Simulation), another UK Government-funded project. Read more about it here.
And of course it also reminds us of of the work by Google’s Aaron Koblin on visualizing SMS messages sent on New Year’s Eve in Amsterdam in 2007 (see below). We imagine as Tweet-o-Meter moves forward through beta they’ll need to figure out how to marry Koblin-esque visualizations to their gushing pipe of data. Bringing magic to the mayhem.
Amsterdam SMS messages on New Years Eve from Aaron on Vimeo.
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Linking intelligently (or why I love bit.ly)
3rd April 09
I transitioned from tinyurl.com to bit.ly earlier this year. Probably way after most people started using it. It’s awesome. But I’m guessing the reason I love bit.ly is not the reason most people would give. Yes, bit.ly delivers super utility simply by shortening a link of seemingly any length to virtually no length. And it makes it easy and quick. That’s part of it.
But I’ve become addicted to the data which bit.ly provides on every link you shorten. Because with bit.ly the shortening is just the beginning of it’s magic. If you register on the site you have a record of all the links you’ve shortened. And if you hit the ‘Info’ function underneath a link you are presented with a treasure trove of metrics & insight. Traffic (clicks) with time & date information, geographical location, platform used to access the link, conversations the link featured within, RTs, and so on.
So one learns that a link posted on Twitter that touches on industrial design is 50% more likely to be clicked on in Brazil than in the UK. Or a link that relates to LEGO is three times as likely to be clicked on in Denmark than in Canada. Or that the optimum time to post is 10pm ET, or that actually one needs to re-post because the two peaks are 10pm ET and 10pm GMT, or that if you want to provoke an Australian audience one should post after 11pm ET. Much of this might seem intuitive, but accessing the data that proves (or refutes) some of the assumptions we work with when we share links is a revealing exercise. Above all, it provides much greater depth of feedback on what’s popular (or not) than simply the crude measure of how often your message is RT on Twitter. And it’s not just Twitter – you can add a bit.ly add-on to your Gmail (http://bit.ly/Xd1yM).
Bit.ly allows you to do a whole lot more than fire-and-forget; it promotes smart linking, and that makes it cool in my (Excel work) book.











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