Social Collider
February 12, 2009From the Author:
The Social Collider reveals cross-connections between conversations on Twitter.
With the Internet's promise of instant and absolute connectedness, two things appear to be curiously underrepresented: both temporal and lateral perspective of our data-trails. Yet, the amount of data we are constantly producing provides a whole world of contexts, many of which can reveal astonishing relationships if only looked at through time.
This experiment explores these possibilities by starting with messages on the microblogging-platform Twitter. One can search for usernames or topics, which are tracked through time and visualized much like the way a particle collider draws pictures of subatomic matter. Posts that didn't resonate with anyone just connect to the next item in the stream. The ones that did, however, spin off and horizontally link to users or topics who relate to them, either directly or in terms of their content.
The Social Collider acts as a metaphorical instrument which can be used to make visible how memes get created and how they propagate. Ideally, it might catch the Zeitgeist at work.
Comments
The above post is referring to http://www.emineer.com I think.
Reply to this commentCan you verify the New York SEO that is required for this to work?
Reply to this commentBack to All10 of 106 Prev | Next Social Collider February 12, 2009 Author: Sascha Pohflepp and Karsten Schmidt Location: London, UK LAUNCH EXPERIMENT Rate Experiment (193 ratings): 12345 Share with a friend | Report this experiment From the Author: The Social Collider reveals cross-connections between conversations on Twitter.
With the Internet's promise of instant and absolute connectedness, two things appear to be curiously underrepresented: both temporal and lateral perspective of our data-trails. Yet, the amount of data we are constantly producing provides a whole world of contexts, many of which can reveal astonishing relationships if only looked at through time.
This experiment explores these possibilities by starting with messages on the microblogging-platform Twitter. One can search for usernames or topics, which are tracked through time and visualized much like the way a particle collider draws pictures of subatomic matter. Posts that didn't resonate with anyone just connect to the next item in the stream. The ones that did, however, spin off and horizontally link to users or topics who relate to them, either directly or in terms of their content.
The Social Collider acts as a metaphorical instrument which can be used to make visible how memes get created and how they propagate. Ideally, it might catch the Zeitgeist at work.
Comments By Joshua on July 17, 2010 Fuck this it doseen`t even work this is just a piece of fucking shit fuck fuck fuck!!:C By NotJoshua on July 26, 2010 You're really mature. By blow me on July 04, 2010 this shit sucks didnt even work keep giving gay error messages thought it was safari so i used internet explorer shit still sucked more dick than a 2$ whore By badita florin on May 18, 2010 Unfortunaltly even when i tried with trending topics, it`s still give me errors By g on May 13, 2010 seems it's good to measuring the success of a viral By JT Pedersen on April 19, 2010 Tried half-dozen queries, everyone returned 'no results,' i
Reply to this commentNEATIII
Reply to this commentYou're really mature.
Reply to this commentUnfortunaltly even when i tried with trending topics, it`s still give me errors
Reply to this commentseems it's good to measuring the success of a viral
Reply to this commentTried half-dozen queries, everyone returned 'no results,' including a simple query for 'apple.' One would think even if I can't find anything related to less popular topics, that 'apple' would return something.
Came, saw, next...
Reply to this commentlol try "Apple", keyword, 1 week
Reply to this commentit seems to take ages to load up
Reply to this commentok i did not geat the true
Reply to this commentHey Karsten,
Remember me?
Very cool work...
Rob ;-)
Reply to this commentHighly cool. Have you considered making queries case-sensitive to properly handle references to hashed URLs, e.g., tr.im/h8qD?
Reply to this commentfucking work
Reply to this commentI KNOW PIECE OF SHIT!
Reply to this commentNaughty Naughty! you swore! you should be smacked on the bottom. Your mother will spank you until you learn your lesson... for now sit in the naughty corner!
Ohhhh my God... (shivers) I would rather read (or better, skim) 10 posts of pure profanity than one utterly creepy post like that. I can't think of a worse shock than having a complaint about a chrome experiment not working being rerouted into a disturbing fetish.
haha, quality. Missing the mothers lurrrve?
i don't think thats what he ment
сбавьте обороты. у меня в Сибири скорость 64 килобит/секунду. приложение грузится за 4 минуты. А задумка прикольная. автору респект!
Reply to this commentTranslation:Slow pace. I have a Siberia speed 64 kilobits / second. It took 4 minutes to load. A cool idea. I respect the author!
Reply to this comment...good luck with that
Reply to this commentAHH! RUSSIANS!!!
Reply to this commentrun from the commies
Sascha, Karsten this is brilliant and super cool and great hypothesis - does seem to use a lot of power well at least I mean my machine raced but is does with many other programs as well.
@dawnweslept
Brilliant !!
Reply to this commentI think I speak for most people when I say i don't get it. An explanation of what each portion of the visualization does would probably do wonders to aid in comprehension.
While the visualization is probably informative if you know how to extract information from it, a well made visualization is normally self explanitory.
Reply to this commentthat was great. Very interesting depiction of Twitter data
Reply to this commentNice experiment. This one really seems useful
Reply to this commentInteresting. And I only had to look up 3 words of what you said :). Cool possibilities.
Reply to this commentVery interesting to display a graphical representation of the social impact of a twitter user, keyword or trend. Reminds me of the code in the movie Matrix but backwards ;-) I like it. Good Job!
Note: It seems to use a lot of processor power.
Reply to this commentLovely stuff..
I use Ubiquity for most of the stuff including Twitter while I help beta-test their interface. This creates rather 'disconnected' tweets even when they are part of a conversation involving @reply. Twitter time-line tries to align such tweets as conversation but its not always very effective.
It appears this has some bearing on the collider map. Perfahps you would want to consider including the interface used to twitting..
Also, I found the rendering a bit slow (about 4 minutes for 1125 tweets).. Is it normal?
Regards, M.
Reply to this commentLove it. So many social data collecting possibilities.
Reply to this commentI think the lack of post is due to the fact no one understands what you just said... wrote... typed... posted... I like ...
Reply to this commentNEAT!!!
Reply to this comment