Computer Science

Front 1

macro

Back 1

the world responds (or not) an individual's actions

Front 2

micro

Back 2

an individual's actions

Front 3

synthetic

Back 3

something is created to produce a desired result

Front 4

analytic

Back 4

laws are stated to explain observed phenomena

Front 5

microsynthetic

Back 5

An individual builds a website to produce a desired result (i.e. our websites built on HTML, CSS, PHP, etc., WordPress blogs, RSS feed from an individual, company, or organization)

Front 6

macrosynthetic

Back 6

“The world” builds a Web site to produce a desired result (i.e. Wikipedia, Delicious social bookmarking, Delicious RSS feed, Twitter)

Front 7

macroanalytic (definition)

Back 7

large-scale Web phenomena investigated and explained

Front 8

macroanalytic (questions
A) What is the structure of the Internet?
B) How did these structures arise?
C) How can we measure this?

Back 8

A) Connected component, clusters, hubs
B) Randomness, Homophily/“birds of a feather”, Cumulative advantage/“the rich get richer”
C) Degree distribution

Front 9

both mathematical modeling and research are useful

Back 9

◦ Mathematical modeling used
 When data is not available
 When computation is too complex  To suggest other areas of study

◦ Examples
 The Internet as a random graph  The Internet as a scale-free network

Front 10

4 key research results

Back 10

1. The Web is shaped like a bow tie
2. The degree distribution of links on the Web is a power law distribution (Six Degrees Chapter 4)
3. “The rich get richer” (cumulative advantage) strongly shapes preferences in a connected world (Duncan Watts article from New York Times)
4. There are 255 million websites in the world as of October 2010 (Netcraft)

Front 11

macro

Back 11

the world responds (or not) an individual's actions

Front 12

micro

Back 12

an individual's actions

Front 13

synthetic

Back 13

something is created to produce a desired result

Front 14

analytic

Back 14

laws are stated to explain observed phenomena

Front 15

microsynthetic

Back 15

An individual builds a website to produce a desired result (i.e. our websites built on HTML, CSS, PHP, etc., WordPress blogs, RSS feed from an individual, company, or organization)

Front 16

macrosynthetic

Back 16

“The world” builds a Web site to produce a desired result (i.e. Wikipedia, Delicious social bookmarking, Delicious RSS feed, Twitter)

Front 17

macroanalytic (definition)

Back 17

large-scale Web phenomena investigated and explained

Front 18

macroanalytic (questions
A) What is the structure of the Internet?
B) How did these structures arise?
C) How can we measure this?

Back 18

A) Connected component, clusters, hubs
B) Randomness, Homophily/“birds of a feather”, Cumulative advantage/“the rich get richer”
C) Degree distribution

Front 19

both mathematical modeling and research are useful

Back 19

◦ Mathematical modeling used
 When data is not available
 When computation is too complex  To suggest other areas of study

◦ Examples
 The Internet as a random graph  The Internet as a scale-free network

Front 20

4 key research results

Back 20

1. The Web is shaped like a bow tie
2. The degree distribution of links on the Web is a power law distribution (Six Degrees Chapter 4)
3. “The rich get richer” (cumulative advantage) strongly shapes preferences in a connected world (Duncan Watts article from New York Times)
4. There are 255 million websites in the world as of October 2010 (Netcraft)

Front 21

Theme: Collaborating Responsibly

Back 21

 You used Discussion Board, class and lecture discussions, and class presentations to help one another
 You used Internet resources made available by others
 This is the way of the Internet

Front 22

Theme: Collaborating Responsibly (Copyright)

Back 22

 We learned how to use copyrighted, public domain, and licensed material (text or images) online
 How do you tell if material is copyrighted?
◦ It has a copyright statement
◦ It says “All rights reserved.”
◦ It has no copyright statement, but also no license
information and no statement that it is public domain
 Assume it is copyrighted unless stated otherwise

Front 23

Using Copyrighted Material as Fair Use (Theme: Collaborating Responsibly cont'd)

Back 23

 Fair use = very limited set of criteria that allows you to use copyrighted material without permission
 Must be for: criticism, comment, news reporting, teaching, scholarship, or research
 Also must use small % of copyrighted work and not affect its value

Front 24

Using Copyrighted Material (If Not Fair Use) (Theme: Collaborating Responsibly cont'd)

Back 24

 If not “fair use,” you can use copyrighted material if you get permission from the copyright owner
 If you do not get permission from the copyright owner, you are practicing “copyright infringement”
 Difference between copyright infringement and plagiarism

What If It’s Licensed?
 If the material has a Creative Commons license, or says “Some rights reserved” with a link to a license, read the license to see what you are allowed to do with it.

Front 25

Creative Commons Attribution License (Theme: Collaborating Responsibly cont'd)

Back 25

 Attribution license allows:
◦ Sharing (copying, distributing, transmission)
◦ Remixing (adapting)
◦ In return, you must
◦ Provide attribution
◦ Make the license terms clear to others (linking to the license).

Front 26

Creative Commons Attribution-Share-Alike License (Theme: Collaborating Responsibly cont'd)

Back 26

 Attribution-ShareAlike license allows: ◦ Sharing (copying, distributing, transmission) ◦ Remixing (adapting)
 In return, you must
 Provide attribution
 If you alter, transform, or build upon the work, you may distribute the resulting work only under the same or similar license to this one.
 Make the license terms clear to others (linking to the license).

Front 27

Creative Commons Attribution-No Derivatives License (Theme: Collaborating Responsibly cont'd)

Back 27

 Attribution-No Derivatives license allows:
◦ Sharing (copying, distributing, transmission)
◦ But not remixing (adapting)
◦ In return, you must
◦ Provide attribution
◦ Do not alter, transform, or build upon the work.
◦ Make the license terms clear to others (linking to the license).

Front 28

Creative Commons Attribution-Non Commercial License (Theme: Collaborating Responsibly cont'd)

Back 28

 Attribution-Non Commercial license allows:
◦ Sharing (copying, distributing, transmission)
◦ Remixing (adapting)

 In return, you must:
◦ Provide attribution
◦ Not use the work for commercial purposes.
◦ Make the license terms clear to others (linking to the license).

Front 29

Themes: Do the Right Thing

Back 29

Our actions as individual web builders have an effect on the entire Web.

Front 30

The Right Thing, Case 1

Back 30

The right thing: Keeping your operating system and software (Word, Flash) up-to-date

Why you might not want to do it: Takes time, can be inconvenient

Why to do it anyway: Prevent your computer from becoming a home for viruses or worms, and from joining a botnet that does harm

Front 31

Theme: Collaborating Responsibly

Back 31

 You used Discussion Board, class and lecture discussions, and class presentations to help one another
 You used Internet resources made available by others
 This is the way of the Internet

Front 32

Theme: Collaborating Responsibly (Copyright)

Back 32

 We learned how to use copyrighted, public domain, and licensed material (text or images) online
 How do you tell if material is copyrighted?
◦ It has a copyright statement
◦ It says “All rights reserved.”
◦ It has no copyright statement, but also no license
information and no statement that it is public domain
 Assume it is copyrighted unless stated otherwise

Front 33

Using Copyrighted Material as Fair Use (Theme: Collaborating Responsibly cont'd)

Back 33

 Fair use = very limited set of criteria that allows you to use copyrighted material without permission
 Must be for: criticism, comment, news reporting, teaching, scholarship, or research
 Also must use small % of copyrighted work and not affect its value

Front 34

Using Copyrighted Material (If Not Fair Use) (Theme: Collaborating Responsibly cont'd)

Back 34

 If not “fair use,” you can use copyrighted material if you get permission from the copyright owner
 If you do not get permission from the copyright owner, you are practicing “copyright infringement”
 Difference between copyright infringement and plagiarism

What If It’s Licensed?
 If the material has a Creative Commons license, or says “Some rights reserved” with a link to a license, read the license to see what you are allowed to do with it.

Front 35

Creative Commons Attribution License (Theme: Collaborating Responsibly cont'd)

Back 35

 Attribution license allows:
◦ Sharing (copying, distributing, transmission)
◦ Remixing (adapting)
◦ In return, you must
◦ Provide attribution
◦ Make the license terms clear to others (linking to the license).

Front 36

Creative Commons Attribution-Share-Alike License (Theme: Collaborating Responsibly cont'd)

Back 36

 Attribution-ShareAlike license allows: ◦ Sharing (copying, distributing, transmission) ◦ Remixing (adapting)
 In return, you must
 Provide attribution
 If you alter, transform, or build upon the work, you may distribute the resulting work only under the same or similar license to this one.
 Make the license terms clear to others (linking to the license).

Front 37

Creative Commons Attribution-No Derivatives License (Theme: Collaborating Responsibly cont'd)

Back 37

 Attribution-No Derivatives license allows:
◦ Sharing (copying, distributing, transmission)
◦ But not remixing (adapting)
◦ In return, you must
◦ Provide attribution
◦ Do not alter, transform, or build upon the work.
◦ Make the license terms clear to others (linking to the license).

Front 38

Creative Commons Attribution-Non Commercial License (Theme: Collaborating Responsibly cont'd)

Back 38

 Attribution-Non Commercial license allows:
◦ Sharing (copying, distributing, transmission)
◦ Remixing (adapting)

 In return, you must:
◦ Provide attribution
◦ Not use the work for commercial purposes.
◦ Make the license terms clear to others (linking to the license).

Front 39

Themes: Do the Right Thing

Back 39

Our actions as individual web builders have an effect on the entire Web.

Front 40

The Right Thing, Case 1

Back 40

The right thing: Keeping your operating system and software (Word, Flash) up-to-date

Why you might not want to do it: Takes time, can be inconvenient

Why to do it anyway: Prevent your computer from becoming a home for viruses or worms, and from joining a botnet that does harm

Front 41

The Right Thing, Case 2

Back 41

The right thing: Contributing to Wikipedia articles in your area of expertise

Why you might not want to do it: Takes time and effort

Why to do it anyway: If you make Wikipedia better with what you know, others will do so too.

Front 42

The Right Thing, Case 3

Back 42

The right thing: Adding relevant links to other websites to your own website

Why you might not want to do it: Increases the other site’s PageRank at the expense of yours

Why to do it anyway: 1) Provides useful information to your website’s visitors
2) If links end, Internet would stop working

Front 43

The Right Thing, Case 4

Back 43

The right thing: Making sure that there is enough contrast between the text and background on your website

Why you might not want to do it: Rules out some great- looking options

Why to do it anyway: Allow people with visual impairments to see your site

Front 44

Tools: Graphs

Back 44

 We studied graphs as a way of modeling the Internet (and other networks)

 Network: “a collection of objects connected in some fashion”

 A graph is an ordered pair G = (V, E)

Front 45

Tools: Sets

Back 45

 Set: “a collection of objects”
 Order does not matter
 An element may be repeated, but it only “counts” once
 Used for:
◦ The collection of vertices of a graph
◦ The collection of edges of a graph ◦ The neighborhood of a node in a graph
◦ Individual edges of an undirected graph

Front 46

Tools: Ordered Lists

Back 46

 Ordered lists: also a collection of objects, but one in which order of elements matters
 Used for:
◦ Edges of a directed graph
◦ Paths
◦ N-tuples

Front 47

Tool: Algorithms

Back 47

 We learned algorithms to
◦ Show how network structures can arise
◦ Show how particular computations can be
performed

Front 48

Random Graph Algorithm I (definition/use)

Back 48

 Source for complete description: Web Science chapter on Network Dynamics
 What is it for?
◦ Early model of Internet structure
◦ Shows quick evolution of giant connected component
◦ Shows normal degree distribution

Front 49

Random Graph Algorithm (steps)

Back 49

 Start with: an undirected graph with nodes but no edges
 Steps: randomly add edges between non- adjacent nodes
 Ends when: every node is connected to every other (clique)
 Notes: giant connected component typically forms when average degree is 1

Front 50

Triadic Closure Algorithm I (definition/use)

Back 50

 Source for complete description: Web Science chapter on Network Dynamics
 What is it for?
◦ Shows formation of clusters (groups of nodes
in a graph that are more connected to each other than they are to the rest of the graph)
◦ Illustrates homophily—e.g., two people with the same friend are likely to become friends themselves

Front 51

Triadic Closure Algorithm II (definition/use)

Back 51

 Start with: an undirected graph with nodes and edges
 Steps: Add edges to connect nodes that are not adjacent but share a common neighbor
 Ends when: All nodes with a common neighbor are also adjacent. Every connected component will be a clique; no previously unconnected components will be connected.

Front 52

Preferential Attachment Algorithm (definition/use)

Back 52

 Source for complete description: Web Science chapter on Network Dynamics
 What is it for?
◦ Shows formation of network hubs
◦ Illustrates cumulative advantage—small, randomly made decisions early in a process can have a huge impact later

Front 53

Preferential Attachment Algorithm (steps)

Back 53

 Start with: A graph with 2 or more nodes and at least one edge
 Steps:
◦ Add a new node
◦ Link the new node to an existing node based
on the degree of the existing node. If deg(x) = 2*deg(y), then x is twice as likely to be picked as y.
 Ends when: graph has desired number of nodes
 Note: typically, the node chosen for the first edge will be a hub

Front 54

Distance Algorithm (definition/use)

Back 54

 Source for complete description: Web Science chapter on Algorithms
 What is it for? Compute the distance between 2 nodes in a graph

Front 55

Distance Algorithm (steps)

Back 55

 Start with:
◦ Source node
◦ Target node
 Steps:
◦ Distance of the source node from itself is 0
◦ All other nodes are in the set of unvisited
nodes
◦ Give all nodes adjacent to the source node
and in the set of unvisited nodes a distance of 1
◦ Remove those nodes from the set of unvisited nodes
◦ Repeat, adding 1 to the distance each time
 Ends when:
◦ The target node is reached or there are no more adjacent nodes

Front 56

Summation Algorithm

Back 56

 Source for complete description: Web Science chapter on Algorithms
 What is it for?
◦ Compute the sum of positive integers starting
with 1 and ending with the input variable n
◦ Shows how to translate a computation into an
algorithm
 Ends when:
◦ The last integer (n) is added to the total

Front 57

NetRank and PageRank Algorithms

Back 57

 Source for complete description: Web Science chapter on Influence
 What is it for?
◦ Determine order of Google search results
 Starts with:
◦ A directed graph
 Ends when:
◦ Values are computed for all nodes in the graph
◦ The values converge

Front 58

"Point Vampires": Sets and Lists

Back 58

 Enclose sets in curly braces { }
 Enclose ordered lists in parentheses ( )
 The empty set is written { }; this is not the same as { 0 }
 The symbol for “a member of” is ∈
 the symbol for “a subset of” is ⊆

Front 59

"Point Vampires": Graphs

Back 59

 A graph is an ordered pair G = (V, E)
 Use curly brackets to indicate edges in undirected graphs
 Use parentheses to indicate edges in directed graphs