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From Opinion to Identity: Social Media Bots
1. From Opinion to Identity
(Or how we made bots out of your life-streaming)
Product Development Entertainment Search
Doing mass ethnography Prototype character designs with Custom Personas system for
in real-time narrative filtering. continuous search streams
2. “Umntu ngumntu ngabantu.”
A human being is a person through
(other) people. (Bantu proverb)
— Bailey, Cameron. “Virtual Skin: Articulating Race in
Cyberspace.”Immersed in Technology. Eds. Moser, Mary Anne and
Douglas MacLeod. Cambridge, Massachusetts: MIT Press, 1996. 29-49.
3. Identity emerges based upon
probability seeds.
We are all probabilities.
We are all probable individuals.
Oh, oobee doo!
I wanna be like you..
I wanna walk like you..
Talk like you, too.
You'll see it's true,
An ape bot like me,
Can learn to be human too.
- King Louie’s song from “The Jungle Book” movie
4. Can we make characters that we
want to follow and who inform us
in an entertaining and useful way
using public ‘Activity Streams’?
5.
6.
7. n. Demo Graphic Replicator
A probability* bot service that
consumes social media feeds
to produce emergent
personalities in real-time.
*Contains no artificial intelligence
13. Every hour the bot character
collects the relevant keywords
from it’s personality file then tries
to find a match with a tweet.
If it finds one, it Retweets it.
21. Credits The Developers
Mowgli and King Louie from “The Jungle Book” David Bausola
http://www.imdb.com/title/tt0061852/ Service design - @zeroinfluencer
Rob Myers
Bantu spirit mask Engineering lead and concept design - @robmyers
http://www.downtownmakeover.com/downtown_reno/shopping_bantu_spirit.asp
Nick Renny
Geo-locational engineering - @laundyman
Dr. Eldon Tyrell and film still from “Blade Runner” And all the Phactory Phellows
http://www.imdb.com/title/tt0083658/
http://twitter.com/zeroinfluencer/the-phellows
Activity Streams
http://activitystrea.ms/
Presented to an excellent audience on 1st March 2010
OAuth
http://oauth.net/
Creative Commons
http://creativecommons.org/
We Feel Fine
http://wefeelfine.org/
User Icon
http://www.iconarchive.com/show/must-have-icons-by-visualpharm/User-icon.html
TwitterTees
http://www.zazzle.com/retweet+me+tshirts
Smiling ‘avatar’ Faces
http://www.istockphoto.com/
This presentation is licenced under Creative Commons BY-SA www.philterphactory.com
except where images have been used under fair use.
Editor's Notes
Hello - this is going to be a quick look into a project that creates personalities out of social media streams that seem to bring value to 3 areas: Product Development, Entertainment and Search.
But it’s not anything new - the Bantu tribe have a saying that a human is someone who lives through other people. This is exactly what our bots do.
And the world of fiction has been exploring this idea for many years and successful explaining that the idea of an individual is based upon other peoples experiences. We’ve avoid Artificial intelligence in favor for statistical probability.
Today we have a insane volume of socially available data from web services - generated by users who wish to share it with anyone who wants to listen. Open standards and protocols are making this easier and faster everyday.
So we started with building the application that supports the creation and automation of the personalities - we call it the Demo Graphic Replicator.
The software first makes an API call to We Feel Fine to find out what the bot should be ‘feeling’.
The application works by the bot collecting the keywords, ‘shuffling them’ and then finding a Tweet to empathize with. We use the ReTweet method to do this.
And the results include some interesting twists on the Turing test - people seem to respond to the bots in a very human way. Many of the test bots have hundreds of followers.
And they seem to be inspiring the most inspiring people. So the bots are working through creative solutions and giving them away for free.
As ‘personalities’ they grow their own social graphs. They are as real as a photo. The camera, like data, never lies. :)
But we have a design problem. Making generative faces mean we our bots always look like someone. Using stock photographs is one way to do this. Perhaps we need to make Chernoff faces.
And then we get weird meta-feedback-loops as with Jimmmo, a bot, being called out by another bot who is based upon a bot in a film. Neither of which have a mother. This experiment in convergence culture shows the role of narrative helps us understand and manage huge volumes of data.