Week 3
From INLS 490
Week 3
Contents |
[edit] Video
Six degrees of separation by Surfca13
[edit] Week 3
- Notes
- Added Reading: Is the Tipping Point Toast? Clive Thompson
- My writing this week:
- ASIST Social Computing Summit
- For next week:
- Kumar/Golder skim mathematical sections
- No Monday office hours 2/4
- Related readings
- Link to Frontline Program
- This Week's Del.icio.us links
== Discussion of Frontline/Privacy/Bullying Etc.
Questions that emerged from the discussion:
- Keeping perspective - most real-life youth internet use is innocent. Do we concentrate on the outliers?
- What kind of information are teens getting online? What type of information is most dangerous?
- The risks and prevalence of cyberbullying - what should adults do?
- Democratization of communication and the long tail - aren't communities of interest inevitable?
- The value of an online identity - youth relationships with their digital selves
- Our tendency to become mean when we're anonymous - SIDE
References on Digital Youth
- Digital Youth Research Project
- Digital Natives Project
- Marc Pensky - Digital Natives, Digital Immigrants
- MacArthur series on Youth, Identity and Digital Media
[edit] Thoughts on Barabasi, Shirky?
Questions and critique of the readings. What interesting themes or ideas emerged? What challenged you? What did you buy or not buy?
[edit] Network dynamics
[edit] Networks 101
- Nodes, edges and paths
- Nodes: The objects to be connected in a network
- Edges: The ties that bind nodes in a network
- Paths: Our means of transversal between places in a network
- Concepts of distance and betweenness
- Network analytic models compute the distance between nodes calculated in path transversals
- Betweenness: The connenctive quality of a node measured by its place in the graph
- Distance: The shortest path length between a node in a graph
[edit] Graph Models
- Erdos-Renyi Random Model
- Erdos-Renyi assume that edges are non-preferential, ensuring a random distribution of connections in a graph.
- How does this model fail in real life?
- Watts-Strogats "Small Worlds" Model
- The Small World model predicts that edges display clustering characteristics that would account for some non-randomness (Bell Curve).
- Scale-Free Network
- Barabasi et. al. predict that edges display preferential attachment, creating a power-law distribution of attachments in the network. This accounts for hubs and authorities in a network.
[edit] Centrality
- What is centrality and why is it important?
- Erdos/Kevin Bacon and Six Degrees of Separation
- A-list bloggers. How does the "scale-free" blogosphere benefit A-list bloggers?
- How would we test these models in Facebook or other Social Network?
[edit] Information flow in networks
- How do we establish edges in networks
- On the web
- On social networks
- In real world social networks
- Structural constraints in networks
- What about the web, or Facebook, or any other information medium enforces "network law"
- How do we "break" network law (on the web, in SNS, etc?)
[edit] Critique of network study
- What does a single-viewpoint study of a network topology tell us?
- What are some of the problems with applying network-theoretic approaches to our real-world networks?
- What does it mean if we value all friends alike?
[edit] Tools for analyzing social networks
- Pajek, UCINet, Jung
[edit] Questions
- Relationship between voting and a blog's ranking - do power laws promote poor content?
- To get a holistic view of a network, how many means of connection should we account? Since different communication tools have different qualities, how can we factor these in?
- Does the world get smaller because of networks?
- Bloggers aren't charitable, are links votes?
- How does the virtual space we occupy affect our information choice capacity?
- How do social networks collapse the borders between individuals?
- Can we nail down exactly the interaction between networks and blog popularity?
- How do we negotiate authority in the blogosphere?
- The role of marketing in popularity (using your networks)
- What other web-type systems display small-world/scale-free characteristics?
- How would we develop a SNS test of the 6 Degrees hypothesis
- Qualitative and intervening factors in graph growth - how do things like age and friendship quality affect network growth?
- What effect do spikes have in network growth? (Digg, Slashdot)?
