Web
Discussion
Science
Topic:
Tea
Feb 29, 08
Milena Mihail
mihail@cc.gatech.edu
1
Elsewhere :
What is Web Science ?
Our grassroots discussions :
Includes some intersection of
comp sci, economics, social sci.
Our non grassroots discussions :
Super-Duper Data Center,
ala Jeanette Wing
Should revisit this point,
in view of NSF-Google-IBM ?
NSF : CDI
Yahoo: Raghavan
WWW06
Brachman
GT talk
Microsoft:
New Cambridge Lab
Jennifer Chayes
Chris Klaus
GT talk
Parenthesis: MSN SemGrail 07
What is Web Science ?
The study of the WWW, broadly defined.
By virtue of the pervasiveness of the object of study.
Systems-like science (like chemistry or biology).
As opposed to “computer science”
which is the study of “computation”,
biology is the study of “life”
from the cell to evolution to animals….
Should be studied in terms of its
descriptive/predictive/explanatory/prescriptive
analytic value.
Parenthesis: MSN SemGrail 07
Why should there be Web Science ?
Encourage collaboration across different areas.
Something between the union and intersection
of several areas.
Need to establish common vocabulary, goals, problems.
“Understanding the elephant versus the tail trunk”.
Educate students for industry.
Encourage academia to understand
the study of the Web as a discipline.
Parenthesis: MSN SemGrail 07
Themes cutting across subareas of Web science
Long Tails / Economics / Culture
Fractal Nature, multi-scale
Dynamics, emergent systems, social networks
Requires new analytics (eg what are right logics,
probabilistic and approximation metrics)
Humans and machines interact and interactions registered.
New dimension in social sciences.
Transformed way we think about information
(analogy to introduction of printing press).
Democracy of information,
producers and consumers of information coincide.
(in this spirit)
What is Web Science ?
Outline:
Our grassroots discussions :
Wide
Range
of intersection
Models
Includes
some
of
Canonical
Example: Modeling
comp sci, economics,
social sci.Small World Phenomenon
Model Parameters/Metrics and their Relevance
Models : Structural
Explanatory (Optimization or Incentive Driven)
Hybrid
Which question are you (am I) trying to answer?
Range of Models
(nice pictures with some meaning)
Internet (general)
Routing Internet
AS Level
Routing
Level
few long links
in a flat world
Sparse Power Law Graphs
with very different assortativity
Range of Models
(nice pictures with some meaning)
Patent / co-author network
in Boston area
notice bottleneck bad cut
Flickr social network
from Flickr
search keyword “graph”
notice no botlleneck bad cut
( Range of Flickr Pictures - meaning ? )
Technology Platforms
Local Facebook Friendship Graph
A Wep Page
Organization
4 Color Theorem
Range of Models
Biological Networks
with unclear meaning,
but make front page
of Nature/Science/PNAS
Range of Models
(nice pictures with no meaning)
Range of Mathematical Models
Rick Durrett, Cornell, Probabilist
n
Canonical Example: Modeling the Small World Phenomenon
Clustering
and
Small Diameter
Milgram’s Experiment 60’s :
Even though relationships are highly clustered,
most people are pairwise reachable via short paths,
“Six Degrees of Separation” (for fun, see also Facebook group)
Strogatz&Watt’s Model 80’s:
In a clustered graph of size n,
a few random links
decrease the diameter to logn.
Kleinberg 90’s: Navigability !
These short paths can be found efficiently with local search!
Kleinberg’s navigability model
Theorem:
Are there natural network models which are navigable
The onlyand
value
have,
for eg,
which
power-law degree distributions ?
the network is navigable
is r =2.
Are there natural models where the threshold is not sharp ?
14
Model Parameters/Metrics (as a function of n) and their Relevance
Important to have FLEXIBLE network models
eg in Prediction / Simulation
economics
engineering
Average degree and Degree distribution
Evolving toward monopolies/oligopolies?
Clustering coefficient (small dense subgraphs)
Assortativity
Diameter
Expansion/Conductance
(bottlenecks)
Can it be searched, crawled efficiently?
Can pagerank be computer efficiently?
Can it route with low congestion?
Does it support efficient info retrieval?
How does information/technology spread?
Eigenvalues, eigenvectors
(quantify bottlenecks and find groups efficiently)
Structural / Macroscopic Models
Random graphs with desirable graph properties,
thought to be aggregating all microscopic primitives
Example 1: Power Law Random Graph
Given
Choose random perfect matching over
Example 2: Growth & Preferential Attachment
One vertex at a time
New vertex attaches to
existing vertices
Example 2, generalization towards flexibility:
Some evolutionary
random graph models
may also capture more factors,
e.g, geography,
and hence varying conductance.
Explanatory / Microscopic Models / Optimization Driven
Example: HOT, evolutionary, new node attaches
by minimizing cost and maximizing quality of service
Point: Optimization primitives
can yield power law distributions.
Explanatory / Microscopic Models / Incentive Driven
Example: A Network Formation Game
How fast can such a stable configuration be reached?
Hybrid Models
RANDOM DOT PRODUCT GRAPH MODEL
Example 1:
Example 2:
SUMMARY
It is important to identify critical metrics and parameters
ie, how they impact network performance.
It is important to develop models
where critical parameters vary
and flexible network models.
It is important to identify network primitives
related to optimization and incentives.
It is important to develop mechanisms
that affect such primitives.
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HOW ABOUT YOU ?
WHICH QUESTIONS
DO YOU WANT TO ANSWER ?