• Save
Adventures in algorithmic cultures
Upcoming SlideShare
Loading in...5
×
 

Adventures in algorithmic cultures

on

  • 2,516 views

A speech given at UC Berkeley in the "Creating Minds" symposium (part of a "Future of the book" week), October 23, 2013.

A speech given at UC Berkeley in the "Creating Minds" symposium (part of a "Future of the book" week), October 23, 2013.

Statistics

Views

Total Views
2,516
Views on SlideShare
690
Embed Views
1,826

Actions

Likes
6
Downloads
0
Comments
0

21 Embeds 1,826

http://nearfuturelaboratory.com 1212
http://naturalfair.tumblr.com 374
http://cloud.feedly.com 121
http://digg.com 34
http://feeds.feedburner.com 23
http://newsblur.com 11
http://feedproxy.google.com 10
http://translate.googleusercontent.com 10
http://feedly.com 7
https://twitter.com 5
http://lanyrd.com 5
http://reader.aol.com 3
http://l.lj-toys.com 3
http://inoreader.com 2
http://localhost 1
http://webcache.googleusercontent.com 1
http://cyberslug.net 1
http://juliengremaud.tumblr.com 1
http://www.hanrss.com 1
https://www.google.com 1
http://www.inoreader.com 1
More...

Accessibility

Upload Details

Uploaded via as Adobe PDF

Usage Rights

CC Attribution-NonCommercial-ShareAlike LicenseCC Attribution-NonCommercial-ShareAlike LicenseCC Attribution-NonCommercial-ShareAlike License

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Adventures in algorithmic cultures Adventures in algorithmic cultures Presentation Transcript

  • adventures in algorithmic cultures nicolas nova Oct 23, 2013
  • This talk about the future of the book is NOT ABOUT QR CODES
  • ma·chine, noun: an apparatus consisting of interrelated parts with separate functions, used in the performance of some kind of work. Sometimes used to refer to digital technologies. cre·o·liz·at·ion, noun: mixing of different cultural elements that lead to an unexpected and original outcome different than the sums of its parts. ma·chine cre·o·liz·at·ion, noun: mixing of cultural elements in which algorithms played a role in the hybridization process.
  • what’s the equivalent for texts? this is not an exhaustive presentation of the existing work on this topic just some pointers and signals that i find intriguing
  • machinegenerated texts
  • Of course, there’s... “Narrative Science, an innovative technology company, turns data into stories. Narrative Science has developed a technology solution that creates rich narrative content from data. Narratives are seamlessly created from structured data sources and can be fully customized to fit a customer’s voice, style and tone. Stories are created in multiple formats, including long form stories, headlines, Tweets and industry reports with graphical visualizations.”
  • “Having a computer write poems for you is old hat. What’s new is that, like Wershler and Kennedy, writers are now exploiting the language-based search engines and social networking sites as source text. [...] At first glance, armies of refrigerators and dishwashers sending messages back and forth to servers might not have much bearing on literature, but when viewed through the lens of information management and uncreative writing—remember that those miles and miles of code are actually alphanumeric language, the identical material Shakespeare used—these machines are only steps away from being programmed for literary production, writing a type of literature readable only by other bots” Uncreative writing, Kenneth Goldsmith, 2012.
  • logfile poetry on the other hand you have this... producing weird forms of text
  • “‘Diff in June’ tells a day in the life of a personal computer, written by itself in its own language, as a sort of private log or intimate diary focused on every single change to the data on its hard disk. Using a small custom script, for the entire month of June 2011 Martin Howse registered each chunk of data which had changed within the file system from the previous day’s image. Excluding binary data, one day’s sedimentation has been published in this book, a novel of data archaeology in progress tracking the overt and the covert, merging the legal and illegal, personal and administrative, source code and frozen systematics.”
  • Diff in June, Martin Howse, 2013. logfiles, a form of object-centered perspective
  • 42 attempts to save the Princess ^^, Near Future Laboratory, 2013. it’s basically a set of hexadecimal logfile that corresponds to the saved games
  • 42 attempts to save the Princess ^^, Near Future Laboratory, 2013. it seems cryptic, it is, but players who spent lot of time changing this kind of code (reverse engineering) know the meaning of certain portions. it’s a book written the console program, readable by the console program but understandable by some
  • the potential is huge, consider this example
  • human-machine collaboration
  • Memento, Near Future Laboratory, 2013. a guide book based on curated tweets/flickr-instagram pictures
  • Memento, Near Future Laboratory, 2013. a guide book based on curated tweets/flickr-instagram pictures
  • Memento, Near Future Laboratory, 2013.
  • @venice311 micro-drama, Near Future Laboratory, 2013. a fictional book based on curated tweets/flickr-instagram pictures
  • Ghost Writers, Traumawien, 2012. Kindle books generated by algorithms that scrap YouTube content and upload them on Amazon
  • Ghost Writers, Traumawien, 2012.
  • The descriptive camera, Matt Richardson, 2012. crowdsourcing image description (Amazon Mechanical Turk) as a new form of text production
  • machine-like Another option is to give a “machine-like” aesthetic, a “networked realism” as might describe James Bridle afterwards
  • Hamlet Facebook Newsfeed Edition, Sarah Schmelling, 2009. Of course, you have project remediating classic literature. Like Sarah Schmelling’s humorous Hamlet Facebook Newsfeed Edition.
  • Ghosts in the machine, L. Polansky and B. Keogh, 2012. Ghosts in the Machine is an anthology of 13 original short stories that each look at the imperfections of life through the imperfections found in videogames, be they bugs, exploits or design flaws, love, loss or death
  • reading add-ons? writing tools?
  • Monde Binaire, Baptiste Milésie (HEAD–Genève), 2012. a paper comic you can read with extra content on cell-phone
  • iBookmark, Johaness Schöning et al., 2009.
  • ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ●● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Comte de Montaigu Mme de Warens George Keith Thérèse Levasseur Denis Diderot ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● A Social Network Analysis of Rousseau’s Confessions, Y. Rochat & F. Kaplan, 2013 A social network analysis of Rousseau’s Confessions by Yannick Rochat & Frédéric Kaplan: “Working on an index, we build a literary social network of Les Confessions based on co-occurrences, by using a process that deals with edition and page constraints. We are currently investigating new ways to visualize and analyze literary social networks over time. Here, we propose the use of a temporal window, which captures the evolving structure of the network during a given in- terval of time.”
  • ● ● ● ● ● ● ● ● ● ● ●● ●●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●●● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ●● ● ●● ● ● ●● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ●●● ● ● ●● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ●● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ●● ●●● ● ● ● ●● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ●● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ●● ● ● ● ●● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ●●● ●● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ●● ● ● ●● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●●● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ●●● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ●●● ● ● ● ● ●● ● ●● ● ● ● ● ●● ● ● ● ● ●● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●●●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ●● ● ●● ● ● ● ●●● ●● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ●●● ● ● ● ● ● ●●● ● ● ●● ●● ● ●● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ●● ● ●● ●● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ●● ●● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ●●● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ●● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ●●● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ●● ● ● ● ● ● ●●●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ●●● ● ● ● ●● ● ●● ● ● ● ● ●● ● ● ● ● ●● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●●●● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ●● ● ●● ● ● ● ● ● ●●●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ●●● ● ● ● ● ●●● ● ●● ●● ●●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ●●●● ● ● ●● ● ● ● ● ●● ● ● ●● ● ● ● ● ●● ●●●●●● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ●● ● ●● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●●● ●● ● ● ● ● ● ●● ● ● ● ● ●● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●●● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ●●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●●●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ●● ●● ● ●● ● ● ● ● ● ● ●● ● ● ● ●●● ●● ● ●● ● ●● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ●●● ● ● ● ● ● ●●● ● ● ●● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ●● ● ●● ● ● ● ● ●● ●● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ●● ●●● ● ● ●● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ●●● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ●●● ● ● ●● ● ●● ● ● ● ● ● ●● ● ● ● ● ●● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●●●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ●● ●● ● ● ● ●●● ●● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ●● ●●● ●● ● ● ● ● ● ●●● ● ● ● ●●● ● ● ● ● ● ● ●●● ● ●● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ●●● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●●● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●●● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ●● ● ● ● ● ●● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ●● ● ● ●● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ●● ● ● ● ●● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ●● ● ●● ● ●● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ●●● ●● ● ●● ● ●● ● ● ● ● ● ● ●● ● ● ●● ●● ● ● ● ●● ●●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ●● ●● ● ● ● ● ●● ● ● ● ● ● ●● ● ●● ● ● ●● ●● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ●● ●●● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ●● ● ●● ●● ● ●● ● ●● ●● ● ● ● ● ● ● ● ●● ● ●● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ●●● ● ● ● ● ● ● ● ●● ●● ● ● ●● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●●● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●●●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ●● ● ●● ● ●● ● ● ●●●● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ●●● ● ● ●● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ●●● ● ● ●● ● ●● ●● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ●●● ● ● ● ● ● ● ●● ●●● ● ● ● ●● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●●● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ●●● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ●●● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ●● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ●●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●●●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ●● ● ● ● ●●● ●● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●●● ● ● ● ● ● ●●● ● ● ●● ●● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ●●● ● ● ● ●●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ●● ●● ● ●● ●● ● ● ●● ● ● ● ● ● ● ● ●●● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ●●● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ●●●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ●● ● ● ● ●●● ●● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ●●● ● ● ● ● ● ●●● ● ● ●● ●● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ●●● ● ● ● ●●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ●●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●●●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ●● ● ● ● ● ●●●● ●● ● ●● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ●●● ● ● ● ● ● ●●● ● ● ●● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ●● ●● ● ●●●●● ● ● ● ● ●●● ● ● ● ● ● ● ● ●● ● ● ●●● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ●● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ●● ● ●● ●● ● ● ● ● ● ● ● ● ●●● ● ●●● ●● ● ● ●●● ●● ● ● ● ● ●● ● ● ● ●●● ●● ● ● ● ● ● ●● ● ●● ● ● ●● ● ● ● ●●● ●● ● ● ●● ● ● ● ● ● ● ●● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ●●● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●●●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ●● ● ● ● ●●● ●● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ●●● ● ● ●● ●● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ●● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ●● ●●● ● ● ● ●● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●●● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ●● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●●●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ●● ● ● ● ●●● ●● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ●●● ● ● ● ● ● ●●● ● ● ●● ●● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ●●● ● ● ● ●●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ●● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ●● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ●●●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● A Social Network Analysis of Rousseau’s Confessions, Y. Rochat & F. Kaplan, 2013 ●
  • Understanding Shakespeare, Stephan Thiel, 2010. Stephan Thiel
  • Understanding Shakespeare, Stephan Thiel, 2010. An add-on... as the map in Lords of the Ring
  • so what?
  • “many people have either a fascination with computers or merely a curiosity to see them cough up poetry. An introduction and invitation to binary speed for the operator’s lasting benefit. A roll of the dice endlessly resumed. Systematics simultaneously stitched together, synthesized, and derived. But missing throughout will be the vivid contrast among the languages of the world. Which constitutes the desiring flesh of a poem. [...] a computer scientist but also Rimbaud ” Edouard Glissant
  • Human “network realism” Non-Human logfile location-based book “computer poetry” book based on social media/game data
  • thank you nicolas@nearfuturelaboratory.com