Lecture 03 - Network models Flashcards

1
Q

Networks

What is another name for a network?

A

A graph

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2
Q

Networks

What does a network consist of?

A

Nodes/vertices and edges

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3
Q

Networks

What is a neighbour?

A

If nodes A and B are connected with an edge, they are neighbours.

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4
Q

Networks

What are the two most common ways to represent networks in a computer?

A
  • Adjacency matrix
  • Adjacency list
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5
Q

Networks

What is an adjacency matrix?

A

A matrix of m * m elements which shows how each node is connected to all other nodes.

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6
Q

Networks

What is an adjacency list?

A

A dictionary mapping nodes to a list of which other nodes they’re connected to. Python annotation: dict[str, list[str]]

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7
Q

Networks

What is this?

A

An adjacency matrix

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8
Q

Networks

What is this?

A

An adjacency list

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9
Q

Networks

What is the degree of a node?

A

The number of edges connected to it.

For directed nodes, there’s a difference between “indegree” and “outdegree” as well

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10
Q

Networks

What’s the typical way of writing the node’s degree?

A

deg(i), with i being the i-th node.

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11
Q

Networks

What is a walk?

A

A list of edges that are sequentially connected to form a continuous route in a network.

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12
Q

Networks

What is a trail?

A

A walk that doesn’t go through any edge more than once.

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13
Q

Networks

What is a path?

A

A walk that doesn’t go through any node more than once.

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14
Q

Networks

What is a cycle?

A

A walk that starts and ends at the same node, without going through any node more than once.

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15
Q

Networks

What is this a description of?

“A list of edges that are sequentially connected to form a continuous route in a network.”

A

A walk

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16
Q

Networks

What is this a description of?

“A walk that doesn’t go through any edge more than once.”

A

A trail

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17
Q

Networks

What is this a description of?

“A walk that doesn’t go through any node more than once.”

A

A path

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18
Q

Networks

What is this a description of?

“A walk that starts and ends at the same node, without going through any node more than once.”

A

A cycle

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19
Q

Networks

What is a subgraph?

A

A part of the graph.

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20
Q

Networks

What is a connected graph?

A

A graph in which a path exists between any pair of nodes.

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21
Q

Networks

What is a connected component?

A

A subgraph of a graph that is connected within itself, but not to the rest of the graph.

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22
Q

Networks

What is this a description of?

“A graph in which a path exists between any pair of nodes.”

A

A connected graph

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23
Q

Networks

What is the name of a subgraph that is connected within itself, but not to the rest of the graph.

A

A connected component

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24
Q

Networks

What is this a description of?

“A part of the graph.”

A

A subgraph

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25
# Networks What is a complete graph?
A graph in which any pair of nodes are connected
26
# Networks What is a Regular graph?
A graph in which all nodes have the same degree. Every complete graph is regular.
27
# Networks What is a Bipartite (n-partite) graph ?
A graph whose nodes can be divided into two (or n) groups so that no edge connects nodes between the groups. The groups can be connected within themselves.
28
# Networks What is a Tree graph?
A graph in which there is no cycle. A graph made of multiple trees is called a forest graph. Every tree or forest graph is bipartite.
29
# Networks What is a Planar graph?
A graph that can be graphically drawn in a two-dimensional plane with no edge crossings. Every tree or forest graph is planar.
30
# Networks What is this an example of? "A graph in which any pair of nodes are connected"
Complete graph
31
# Networks What is this an example of? "A graph in which all nodes have the same degree."
Regular graph
32
# Networks What is this an example of? "A graph whose nodes can be divided into two (or n) groups so that no edge connects nodes within each group"
Bipartite (n-partite) graph
33
# Networks What is this an example of? "A graph in which there is no cycle."
Tree graph
34
# Networks What is this an example of? "A graph that can be graphically drawn in a two-dimensional plane with no edge crossings."
Planar graph
35
# Networks What is this an example of?
Complete graphs
36
# Networks What is this an example of?
Regular graphs
37
# Networks What is this an example of?
Bipartite (n-partite) graphs
38
# Networks What is this an example of?
Tree graphs
39
# Networks What is this an example of?
Planar graphs
40
# Networks What is an undirected edge?
An edge that is connected in both ways to the node, like a pavement.
41
# Networks What is a directed edge?
An edge that is only connected in one direction, like a one-way street.
42
# Networks What's an unweighted edge?
An edge that has no attached weight/cost. Adjacency matrices have just 0 or 1 as elements.
43
# Networks What is a weighted edge?
An edge with an attached weight/cost, usually positive values, like connection strength or distance.
44
# Networks What is node strength?
The sum of the weights of the edges attached to the node.
45
# Networks What's special about the adjacency matrix of an undirected graph?
It's symmetric.
46
# Networks Can two nodes share multiple edges?
Yes, nodes can have multiple edge, directed or undirected, with different weights.
47
# Networks What is a simple loop?
An edge that starts and ends at the same node.
48
# Networks What's an edge called when it has no direction.
An undirected edge.
49
# Networks What's an edge called when it has a direction?
A directed edge.
50
# Networks What's an edge called when it has a cost/weight?
A weighted edge.
51
# Networks What's an edge called when it doesn't have a cost/weight?
An unweighted edge.
52
# Networks What is the sum of all edge weights for a node called?
The node strength.
53
# Networks If you have an adjacency matrix that's symmetric, what's that type of network called?
An undirected network.
54
# Networks What do you call an edge that starts and ends at the same node?
A simple loop.
55
# Networks What is a simple graph? (4)
A graph that doesn't contain directed, weighted or multiple edges, and has no self-loops.
56
# Networks What do you call a graph that doesn't contain directed, weighted or multiple edges, and has no self-loops.
A simple graph
57
# Networks What is a multigraph?
A graph that may contain multiple edges and both (un)directed edges. Some definitions include self-loops.
58
# Networks What do you call a graph that may contain multiple edges and both (un)directed edges. Some definitions include self-loops.
A multigraph.
59
# Networks What is a hyperedge?
An edge that can connect more than two nodes.
60
# Networks What do you call an edge that can connect more than two nodes?
A hyperedge
61
# Networks What are models for "dynamics ON networks"?
Models that deal with how nodes in a network change over time. The network topology is fixed/unchanging.
62
# Networks What are models that deal with nodes changing, but fixed network topologies?
Models for "dynamics ON networks"
63
# Networks What are models for "dynamics OF networks"?
Models that deal with changes to the network topology only.
64
# Networks What are models that deal with changes to the network topology only called?
Models for "dynamics OF networks"
65
# Networks What are models for "adaptive networks"?
Models that describe the co-evolution of both "dynamics on" and "dynamics of" networks.
66
# Networks What are models that describe the co-evolution both "dynamics on" and "dynamics of" networks called?
Models for "Adaptive networks".
67
# Networks How does the "majority rule model" work?
- Initialize a population with random states (e.g. 0 or 1) - During the update step, each individual changes to the majority of its neighbours.
68
# Networks How is the "voter model" different from the "majority rule model"?
In the voter model, a single node pair of connected nodes is chosen at a time. Between them, a vote is transferred.
69
# Networks What are some variations of the "voter model"? (ORE)
- Original - Reversed - Edge-based
70
# Networks In the voter model, how does the "original variation" work?
A listener is chosen, and then a speaker is chosen from the listener's neighbourhood.
71
# Networks In the voter model, how does the "reversed variation" work?
A speaker is chosen, then a random listener is chosen fro the speaker's neighbourhood.
72
# Networks What is a different name for the voter model "original variation"?
Push
73
# Networks What is a different name for the voter model "reversed variation"?
Pull
74
# Networks In the voter model, how does the "edge-based variation" work?
Edges are chosen at random, then the connected nodes are selected as speaker and listener, respectively.
75
# Networks How does the "Epidemic model" work? (SIR model)
- Initialize nodes as either susceptible (S) or infected (I). - I can infect S with some prob. - I can recover with some prob to either state recovered (R) or S.
76
# Networks How does the "Diffusion model" work?
During updates, nodes are affected by all their neighbours. Think heat transfer. N_i.state += C*sum(N_i.neighbors.state) / deg(N_i)
77
# Networks What are small-world network?
Networks with short paths among all nodes, despite not being a complete graph.
78
# Networks What are networks with short paths among all nodes called?
Small-world networks.
79
# Networks What are scale-free networks?
Networks where the distribution of edges between networks follow a power law distribution; that is, most nodes have few neighbors, but some nodes are very central and have many neighbors.
80
# Networks What do you call a network where most nodes have few neighbors, but a few number of nodes have many neighbors?
A scale-free network.
81
# Networks What is homophily?
An empirically observed sociological fact that people tend to connect those who are similar to themselves
82
# Networks Can walks have loops?
Yes
83
# Networks Can trails have loops?
No
84
# Networks Can paths have loops?
No