Creative-Networking-F08
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Syllabus / Creative-Networking-F08

Creative Networking

Burak Arikan, arikan@burak-arikan.com
Tuesdays 6:30-9:00pm Room 447. Office Hours Sign-Up
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This course is an introduction to complex networks within the context of the arts. It focuses on understanding the structure and dynamics of large-scale networks and expanding the individual's thinking about the network as a creative medium. Emphasis will be on network topology, network modeling, protocol authoring, and information design. In addition to discussing ideas related to designing networks, the class focuses on developing the skills required for implementing networked systems. Students will start from drawing simple diagrams and gradually build running complex networks. Each student will learn and develop critical thinking about networks most through creating many examples of networked systems and through collaboration on protocol authoring.

There are nine problem sets and a final project. In addition, there will be weekly reading assignments supported by discussions in class. Exercises range from hand drawings to programming networked systems. Homeworks are put here: http://itp.nyu.edu/varwiki/ClassWork/Homework-Creative-Networking-F08

The course has 2 phases: Network Structure and Network Dynamics. The first phase focuses on networks as static entities. It is based on the Graph Theory and concerned with the structure. The second phase focuses on the processes taking place in the networks. It is concerned with time, interaction, and multiple characteristics of the elements.

PHASE I: Structure

01 INTRO: Graph Theory, Sep 2


01.Intro
  • Graph Theory and Basic Terminology
  • Networks in the Real World
  • Representing relationships
  • Reading: Albert-László Barabási, "Random Universe", "Six Degrees of Seperation", Linked, pp 9-54.
  • Exercise:
    • Part 1: Find a network in your daily life, draw it on a paper illustrating the nodes and connections. Give it a title.
    • Part 2: Find a directional network in your daily life, draw it on a paper illustrating the nodes, connections, and the directions. Give a title and tell the story of your diagram.
    • Part 3: Find a weighted network and draw it showing the weights. Give a title and tell the story of your diagram.

02 TOPOLOGY, Sep 9


02.Topology
  • Centralized, Decentralized, Distributed, Fully Connected
  • Dense, Sparse, Tree, Small world, Core-periphery, Scale-free
  • Reading: Skye Bender-deMoll, “Potential Human Rights Uses of Network Analysis and Mapping“ [PDF], AAAS Report, 2008, pp 1-6.
  • Artists: MTAA, Mail Art / Fluxus, Hans Haacke
  • Exercise:
    • Part 1: Draw a decentralized network. Layout your diagram carefully focusing on the topology of your network. Translate your diagram into text and enter to the provided template program. Describe the differences.
    • Part 2: Create a distributed network. First draw as a diagram, then write in text, and run your diagram using the template program.
    • Part 3: Create a large network with many nodes (min 100). Generate your network directly as structured text and show with the template program. Remove some nodes, break interconnections, and add other ones, describe how the topology changes.

03 CENTRALITY, Sep 16


03.Centrality
  • Centralization
  • Discovering Density
  • Reading: Albert-László Barabási, “80/20 Rule”, Linked, pp 65-78.
  • Artists: Josh On
  • Exercise:
    • Part 1: Manually collect book relations from Amazon.com. Use Amazon's "Customers who bought this book also bought" feature to connect the books. Start from a book that you recently read or had big influence on you, and collect the related books. Trace the network out one and two steps from the focus book. For each book collect up to 10 related / child books. Write your data in the GraphML structure and run the network in the template program. Show the degree centrality of the top three nodes.
    • Part 2: Choose a topic from Wikipedia. Focus your nodes on nouns like artists, schools, or places. Use Wiki articles' "See also" feature to connect the nodes. Trace the network out one and two steps from the focus node. For each node collect up to 10 related / child nodes. Write your data in the GraphML structure and run the network in the template program. Show the degree centrality of the top three nodes. Break interconnections to make a less connected node to become the top connected. In comparison to the first version, show how the new local densities of the most connected nodes change.
    • Part 3: Calculate the density (average centrality) of your network in Part I. Compare your density with one of your friend's network density.
      • density = edges / nodes*(nodes-1)

04 DISTANCE, Sep 23


04.Distance
  • Shortest Path
  • Closeness Centrality
  • Betweenness Centrality
  • Transitivity
  • Reading: Valdis Krebs, “It’s the Conversations, Stupid!” [PDF], 2004
  • Artists: Olia Lialina, Martin Wattenberg & Marek Walczak, Oliver Laric
  • Exercise:
    • Part 1: Choose one of your earlier networks. First mark the top three important nodes by just looking at it. Then calculate the betweenness centrality of those three nodes. Are they same?
    • Part 2: Remove nodes or edges that are strategically important. Recalculate the betweenness centrality and highlight the differences compared to the first state.
    • Part 3: Merge your network with a friend's network (in the same canvas). Your networks should be conceptually related. Find the most and the least central nodes, highlight the shortest path between them.

05 CLUSTERS, Sep 30


05.Clusters
  • Clustering
  • Clustering coefficient
  • Structural Holes & Bridging
  • Structural equivalence
  • Reading: David Reed, “Group Formation Networks (GFN)“, Context Magazine, 1999
  • Artists: Ubermorgen, Alessandro Ludovico
  • Exercise:
    • Part 1: Find the clusters in your social network, using the data from social web services such as Twitter, Delicious, or Facebook. Name the clusters and compare them.
    • Part 2: Show the structural holes. Bridge them by adding broker nodes in between. Do you have new clusters?
    • Part 3: Merge your network with a friend's network. Do you have larger clusters or new clusters emerged from the new edges and nodes? Show them all in the same canvas.

PHASE II: Dynamics

06 INTRO: Dynamics, Oct 7


06.Intro:Dynamics

07 PROTOCOL, Oct 21


07.Protocol
  • Agreement
  • Encoding
  • Transmitting
  • Decoding
  • Reading: Alexander Galloway, "Physical Media", Protocol, pp 28-53.
  • Artists: RSG, Eduardo Kac, JODI
  • Exercise:
    • Part 1: Compose a small dynamic network, where nodes constantly exchange (send and receive) certain data with their neighbors and respond to the received data. Questions to guide your design:What process takes place in the node continuously? When does the node send a message? What message/data does it send? What response does it give to a received message?
    • Part 2: Expand your small network with more nodes. How does the activity change?
    • Part 3: What is the name of your protocol?

08 ROUTING, Oct 28


08.Routing
  • Delivery Semantics
  • Topology Distribution
  • Shortest Path
  • Reading: Nicolas Bourriaud, "Relational Form", Relational Aesthetics, pp 11-24.
  • Artists: Kate Rich
  • Exercise:
    • Part 1: Improve your previous dynamic network so that nodes that reside far from each other can send and receive messages.
    • Part 2: Turn your canvas into a region (Autonomous System) and collaborate with a friend to connect your regions via TCP/IP. What data do you exchange? What does each of your networks do when they receive the data?
    • Part 3: Refine your multi-region system, collaborate with your friend to orchestrate a unified networked composition.

09 CONTAGION, Nov 4


09.Contagion
  • Virus
  • Epidemic
  • Reading: A. Galloway & E. Thacker, “The Exploit”, “Counterprotocol”, The Exploit, pp 81-101.
  • Artists: Eva & Franco Mattes
  • Exercise:
    • Part 1: Create a virus that infects the nodes in your friend's network. Visualize the spreading activity. Can your virus diffuse partially or fully, how long does it take? What happens to individual nodes when they are infected? Can your actor spread to different layers of networks.
    • Part 2: Create a vaccine (anti-virus) for the virus in your network, so that the nodes gain immunity. Visualize your network's healing activity.
    • Part 3: Create a new tactic for your virus that can exploit immuned nodes.

10 SWARMING, Nov 11


10.Swarming

11 Final Project Proposals, Nov 18

Assignment: Develop a working prototype of your system or part of your system.

12 Final Project Workshop 1, Nov 25

Assignment: Complete and refine your working prototype. Make significant progress toward realizing and improving the project.

13 Final Project Workshop 2, Dec 2

Assignment: Refine and build a robust version. Document your prototype with a max two minute movie. Post your documentation to your class website.

14 Final Project Presentations, Dec 9

Artists

Alexei Shulgin, Christophe Bruno, Eduardo Kac, Eva & Franco Mattes, Etoy, Entropy8zuper!, Heath Bunting / Irrational, JODI, Jonah-Brucker Cohen, Josh On, Kate Rich, Lisa Jevbratt, Mark Napier, MTAA, Natalie Jeremijenko, Olia Lialina, Rafael Lozano-Hemmer, RSG, RTmark, Shane Hope, Ubermorgen, Vuc Cosic

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  Page last modified on December 02, 2008, at 09:50 AM