deb roy – birth of a word
Our first vision of a non-linear (video) portfolio – resonated greatly with what Deb did in his house.
We thought – if we could get people talking to themselves everyday.. so that they might have the footage, like Deb did of his son, over the course of many years, from detox videos. And then, if needed, people could take a look at growth, per verbiage, content, fluidity of speech, depth of connections, awesomeness of doings, et al. We were thinking that might be a more humane means to monitor growth. Again – if one must.
great for birth of a word ness and sports illustrated ness and art ness… but first.. let’s free people no..?
let’s do this first: free art-ists.
It is hard for us to accept that people do not fall in love with works of art only for their own sake, but also in order to feel that they belong to a community. By imitating, we get closer to others—that is, other imitators. It fights solitude. – Taleb, black swan
perhaps why ie: th experiment and this mit & twitter – won’t get us there – until we free people up to be themselves. twitter data is irrelevant – if it’s not really us. no? how to make it not an imitation. every day.
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town run on twitter – via Deb
Katina Michael (@katinamichael) tweeted at 2:49 PM on Sat, Jan 28, 2017:
Deb Roy: Big data 4 social impact https://t.co/pnUTt2o5uc via @YouTube @turpin_etienne @iHolderness @DigiDoGood @PatrickMeier @khanjanmehta
big data for social impact – 2015
2 min – a model that let us predict how he learned words
3 min – 5 yrs later moving to bluefin labs.. not just the convo in the home.. but all public social media in us.. map all convos in us 24/7
let’s do 2 convos..
4 min – twitter approaches us.. new consumer experiences based on this merger.. more and more entangled with what’s on tv..
5 min – transitioning to twitter and back to media lab.. partnership: lab for social machines.. brand new (2015)
applying what learned on communications and bluefin and twitter..
6 min – first project.. boston marathon bombings.. we have complete access to all tweets.. news but also rumors… looking at the anatomy of a rumor… build early detectors when piece of info that is false is starting to get momentum
7 min – tendency toward more ad hoc and disrupting social activity.. harder to get systemic social change.. which is direction we want to take with lab
8 min – social feedback loops that harness for more constructive trends.. ie: in hoon – police have twitter handle on sleeve.. so tweet it and everyone sees
10 min – a system..
11 min – not just understand little town.. but apply some idea.. how we imagine these might translate..
12 min – made up scenario in delhi..
14 min – crowdsource safety apps.. what is missing.. at a system level.. the coupled interactions.. people believing.. and not being overwhelmed by too many request.. and to monitor/scale/report so journalist have measurable impact.. analytics possible
same thinking way school/children shifting..
15 min – so looking at public safety and literacy learning.. decentralized networks..