Social Networks and More: Harambenet 2006 1 Social Networks as a Foundation for Computer Science Owen Astrachan, Jeff Forbes, Susan Rodger, Casey Alt,

Social Networks and More: Harambenet 2006 1

Social Networksas a Foundationfor Computer Science

Owen Astrachan, Jeff Forbes, Susan Rodger,Casey Alt, Richard Lucic, Robert Duvallhttp://www.cs.duke.edu/csed/harambenet


Where are we going … Questions What should our concerns be for those choosing to major in Computer Science? courses, research, jobs, …

Should we be concerned by the precipitous decline in those taking our courses or majoring or …? majors, technical students, non-technical …

What can we do to ensure the ongoing success of our academic discipline? Look inward, look to others


Acknowledgements Social Networks/Broadening Participation group:

Jeff Forbes helped with this talk Casey Alt, Richard Lucic, Susan Rodger Students: Ben Spain & Dametrious Peyton

Drawn from the work of: Michael Kearns, UPenn Eytan Adar, formerly of HP Labs John Breese, David Heckerman, Microsoft Research Jonathan Herlocker, Oregon State University Thomas Hoffman, Brown University Marti Hearst, UC Berkeley Jennifer Golbeck, University of Maryland



WWDD?


Questions

If you gotta ask, you’ll never knowLouis Armstrong: “What’s jazz?”

If you gotta ask, you ain’t got itFats Waller: “What’s rhythm?”

What questions did you ask in school

today?Arno Penzias via Isaac Isadore Rabi


Questions and Answers

Judge a man by his questions rather than by his answers

Voltaire


Computer Science

What is the foundation of computer science? Historically, now, in the future

What changes are here, on the horizon? From theory to practice to education

Can we relate to what and how students learn? Is every generation different, the same, …


History and Computer Science Those who cannot remember the past are condemned to repeat it.

Don’t know much about history, don’t know much about biology, don’t know much about a science book


Who, when?

“No stretching … is required to envision computer consoles installed in every home.

Everyone will have better access to the Library of Congress than the librarian himself now has.

Full reports on current events, whether baseball scores, the smog index in Los Angeles or the minutes of the 178th Korean Truce Commission will be available for the asking.”John, McCarthy, Information, Chapter

1, 1966


You win some, you lose some

People will soon become discontented with the “canned” programs available; they will want to write their own. The ability to write a computer program will be as widespread as the ability to drive a car.

Not knowing how to program will be like living in a house full of servants and not speaking their language.

Many people can write simple programs after an hour or two of instruction. … Programming is far easier to learn than a foreign language or algebra.


Then and Now

Bailey, SIGCSE 1972

It is remarkable that the majority of students can indeed handle fairly complex (Fortran) I/O by the end of the first six lessons, even though they have not actually been formally taught how to do it.

Roberts et al, SIGCSE 2006

The problem most often cited by those attempting to teach Java to novices is the lack of a simple input mechanism,

kentlew.com


What has changed in 20 years?

Machines Characteristics and Availability

Internet Availability, IM, web, Google, …

Students Comfort with technology, Expectations


Teaching Compsci in 1984 64K memory, 128K extended

8-bit, 1 Mhz 6502 processor

5Mb drive: $3500 UCSD Pascal: >$100 Owen's machine: $3000

$677.80 in 1984 has $1200 "purchase power" in 2003

http://eh.net/hmit/ppowerusd/


Typical machine in 2006?

1 Gb memory 3 GHz, 32-bit chip

Cache, … 160 Gb disk Lots of free resources Good academic pricing

Under $600 (priced 6/19/06)


The more things change…?

Assume I took your first course(s) in 1984 and understood the concepts so completely that I could still get a 100 on the final from 1984 if I took it today (e.g., I've been in a cryogenic chamber). How would I do on the 2004 final exam?


What has changed in Physics?

"You'd get a 100 plus or minus sigma. Intro classical physics hasn't really changed that much over the last 100 years. In graduate level e.g. E&M or quantum classes I think ditto, although sigma would be bigger (and might depend more on the instructor variation than on any real variation in the material). The main difference is, I think, that your chances of GETTING 100 now would be much higher."

Rob Brown, Poohbah of Physics Instruction


What has changed in Biology?

"The basic principles and concepts of biology haven't changed much in 20 years. What has changed relates to specific content, and in this arena the changes have been enormous. 20 years ago, we barely knew how to sequence DNA; today information of this kind has had a major impact on just about every topic in the biological sciences. Thus, some questions on an exam today would address topics that would be completely unfamiliar to a 1984 time-traveller. "

Greg Wray,

Director of Undergraduate Studies, Biology


What has changed in Economics?

"… we now cover material that was only introduced in an advanced or intermediate course in 1984. In 1984 we spent the bulk of the time dealing with the Keynesian model and virtually no dialogue about supply side policies. Now the Keynesian stuff is a small subset of a much broader exposure to Aggregate demand and supply… Also there is more international coverage now - as opposed to 20 years ago for obvious reasons."

Lori Leachman, Director of Undergraduate Studies, Economics


What has changed in Calculus?We have two varieties of calculus courses, the lab

courses and the traditional ... The latter two have not changed significantly in decades, and I think that a student who fared well on the 1984 exam in those courses would do well today, and vice versa.

[In the lab courses] You would ace about half the exam. The other half would be unfamiliar to you. For example, you would probably not know how to answer a problem on modeling a set of data, creating an approximation using Euler's method, interpreting derivatives in the context of applications in other fields, or giving explanations of ideas …

Lewis Blake,Supervisor of First-year Instruction


Changes in Computer Science?


Changing CS? Rock, Hard place

If Computer Science has changed drastically is it to keep up with fads and stylistic changes or because of fundamental changes in the discipline?

Are we leveraging the technological and intellectual resources at our disposal

If we haven’t changed, is it because of a solid bedrock of principles that endures? Or because we’re lazy, good-for-nothing, …


What is CS? Who wants to study it? Why do they want to?



NYTimes in 1984


What is CS? Why study it?

Do we have Physics (Math, …) Envy? “It's hard for voice over Internet Protocol or e-commerce to compete with finding the age of the universe,” Peter Lee, CMU

Does familiarity breed contempt? What was different in 1984 than today?



What is Computer Science?

What is the linking thread which gathers these disparate branches into a single discipline? My answer to these questions is simple --- it is the art of programming a computer.

What is the central core of the subject? What is it that distinguishes it from the separate subjects with which it is related?


Is this Computer Science?

public static void stuff(int n){doit(n,0,1,2);

}public static void doit(int n,int f, int t, int a){ if (n == 1) move(n,f,t); else { doit(n-1,f,a,t); move(n,f,t); doit(n-1,a,t,f); }}


Occupational Distribution of Projected S&E Job Openings 2002-2012

Natural Science

Managers

Information Technology

Engineers

Physical Scientists

Life Scientists

John Sargent, US Department of Commerce, 2004


Annual Degrees and Job Openings in Broad S&E Fields

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

Engineering Physical Sciences Computer Sciences Biological / Agricultural Sciences

PhD

Master's

Bachelor's

Projected Job Openings

John Sargent, US Department of Commerce, 2004


US Census Bureau

Demographics: 18 - 24 year olds

White Asian/PacificIslander

Hispanic

African American

Native American

2000 66% 4% 15% 14% 1%

2010 63% 5% 17% 14% 1%

2025 55% 7% 22% 15% 1%


Bachelor’s Degrees from Doctoral Institutions





COHFE Amherst College, Barnard College, Brown University, Bryn Mawr College, Carleton College, Columbia University, Cornell University, Dartmouth College, Duke University, Georgetown University, Harvard University, Johns Hopkins University, Massachusetts Institute of Technology, Mount Holyoke College, Northwestern University, Oberlin College, Pomona College, Princeton University, Rice University, Smith College, Stanford University, Swarthmore College, Trinity College, University of Chicago, University of Pennsylvania, University of Rochester, Washington University in St. Louis, Wellesley College, Wesleyan University, Williams College, Yale University



If you don’t take a course in CS, you won’t major in it.Why is the first year different from all other years?


Who's going to College?






How do we get Studentsinto the Compsci Tent?

Why is the first year different from all other years?


Interdisciplinary minors At Duke it is difficult to double major in sciences Too many requirements, 17 courses in biology

Students are interested in credentials No business major/minor, certificate program (requires intro, capstone, six courses)

Minor requires five courses, double counting ok Three courses in CS, two in econ or biology From gene to social networks, data mining, …


Genome Revolution Focus Course Arts in Contemporay Society, Exploring the Mind, Evolution and Humankind, 20th Century Europe, Visions of Freedom, The Genome Revolution and its Impact on Society, … Three of four courses, one writing, two others. Interdisciplinary 0.5 credit seminar P/F

Seminars, students live in same dorm 600+ out of 1600 in FOCUS course

For Genome, 80 applicants for 30 slots, 65% women In CS Genomics course 8 women, 9 men


Simple examples Given strand of DNA, calculate CG ratio

Potential source of proteins “CGGATTATC”

Given protein “HLVWW” calculate number of different DNA strands that could code for it 64 codons, 20 amino acids

Find heaviest protein in array of proteins Given atomic mass of amino acids

Interpret ORF data from NCBI website


Read DNA assumed to be in 5’ to 3’ orientation Use BioJava to read via http

Construct reverse complement (3’ to 5’) From CAATT produce AATTG

How big is the human genome? Runtime of algorithm O(1)

From Algorithms to Objects


Computer Science is filled with real-world examples.Why is the first year different from all other years?


Teaching as … English is not history

and history is not science and science is not art and art is not music, and art and music are minor subjects and English, history and science major subjects, and a subject is something you 'take' and when you have taken it, you have 'had' it, and if you have 'had' it, you are immune and need not take it again." (The Vaccination Theory of Education?)


Back to the Future

How will we know when we get there?


A Future for Computer Science?


Is there a Science of Networks? From Erdos numbers to random graphs to Internet

From FOAF to Selfish Routing: apparent similarities between many human and technological systems & organization

Modeling, simulation, and hypotheses Compelling concepts

• Metaphor of viral spread• Properties of connectivity has qualitative and quantitative effects

Computer Science?

From the facebook to tomogravity How do we model networks, measure them, and

reason about them? What mathematics is necessary? Will the real-world intrude?


Physical Networks The Internet

Vertices: Routers Edges: Physical connections

Another layer of abstraction Vertices: Autonomous systems Edges: peering agreements Both a physical and business network

Other examples US Power Grid Interdependence and August 2003 blackout


What does the Internet look like?



US Power Grid


Business & Economic Networks Example: eBay bidding

vertices: eBay users links: represent bidder-seller or buyer-seller fraud detection: bidding rings

Example: corporate boards vertices: corporations links: between companies that share a board

member Example: corporate partnerships

vertices: corporations links: represent formal joint ventures

Example: goods exchange networks vertices: buyers and sellers of commodities links: represent “permissible” transactions


Content Networks

Example: Document similarity Vertices: documents on web Edges: Weights defined by similarity See TouchGraph GoogleBrowser

Conceptual network: thesaurus Vertices: words Edges: synonym relationships


Enron


Social networks Example: Acquaintanceship networks

vertices: people in the world links: have met in person and know last names hard to measure

Example: scientific collaboration vertices: math and computer science researchers links: between coauthors on a published paper Erdos numbers : distance to Paul Erdos Erdos was definitely a hub or connector; had 507

coauthors How do we navigate in such networks?



Acquaintanceship & more


Network Models (Barabasi) Differences between Internet, Kazaa, Chord Building, modeling, predicting

Static networks, Dynamic networks Modeling and simulation

Random and Scale-free Implications?

Structure and Evolution Modeling via Touchgraph


Web-based social networkshttp://trust.mindswap.org

Myspace 73,000,000 Passion.com 23,000,000 Friendster 21,000,000 Black Planet 17,000,000 Facebook 8,000,000

Who’s using these, what are they doing, how often are they doing it, why are they doing it?


Golbeck’s Criteria

Accessible over the web via a browser

Users explicitly state relationships Not mined or inferred

Relationships visible and browsable by others Reasons?

Support for users to make connections Simple HTML pages don’t suffice


CSE 112, Networked Life (UPenn)

Find the person in Facebook with the most friends Document your process

Find the person with the fewest friends What does this mean?

Search for profiles with some phrase that yields 30-100 matches Graph degrees/friends, what is distribution?


CompSci 1: Overview CS0

Audioscrobbler and last.fm Collaborative filtering What is a neighbor? What is the network?


What can we do with real data? How do we find a graph’s diameter?

This is the maximal shortest path between any pair of vertices

Can we do this in big graphs?

What is the center of a graph? From rumor mills to terrorists How is this related to diameter?

Demo GUESS (as augmented at Duke) IM data, Audioscrobbler data


Collaborative Filtering Goal: predict the utility of an item to a

particular user based on a database of user profiles User profiles contain user preference information

Preference may be explicit or implicit• Explicit means that a user votes explicitly on some scale

• Implicit means that the system interprets user behavior or selections to impute a vote

Problems Missing data: voting is neither complete nor uniform

Preferences may change over time Interface issues


My recommendations at Amazon


And again…


Finally, …


Whose recommendations?


And again…


Alan Kay

"Simple things should be simple. Complex things should be possible".

"The best way to predict the future is to invent it"

Documents

Social Networks and More: Harambenet 2006 1 Social Networks as a Foundation for Computer Science Owen Astrachan, Jeff Forbes, Susan Rodger, Casey Alt,