CMN 150V Final questions and
answers graded A+ 2025/2026
Wait! How much do some top celebrities get paid per tweet? - CORRECT ANSWER ✔✔US$
10,000 or more
What does the "two-step flow model" say? Information flows: - CORRECT ANSWER ✔✔from the
media, to influencers, to the public
What are the two complementary aspects of Computational Social Science Prof. Lamberson
from UCLA will talk about? - CORRECT ANSWER ✔✔empirical work + computer simulations
The only truly influential people in society are celebrities and famous people, like Justin Bieber,
Barack Obama, and Kim Kardashian. - CORRECT ANSWER ✔✔False
What trick did Prob. Lamberson use in order to track who re-posted a URL-link to a story on
Twitter? - CORRECT ANSWER ✔✔He tracked short URL, which are unique to the post
What are 'Twitter cascades'? - CORRECT ANSWER ✔✔An information diffusion process on Titter
in which a number of people make the same decision of passing along information in a
sequential fashion
What is the first thing researchers found when looking at the empirical evidence about Tweets
that go viral? - CORRECT ANSWER ✔✔The vast majority of posts never get retweeted, but a
small fraction of links go viral
,Does this sound familiar? In a data science framework, what are the first and second part of the
data refer to? - CORRECT ANSWER ✔✔Training set & test set
If it turned out that one of the top-25 most retweeted URLs came from an account that had
little influence in the past, and has a small number of followers, where would it be located in
this graph? - CORRECT ANSWER ✔✔Bottom left
If it turned out that one of the top-25 most retweeted URLs came from an account that had
MID-LEVEL influence in the past, and has a small number of followers, where would it be
located in this graph? - CORRECT ANSWER ✔✔Mid-bottom
Let's assume that if you have this disease, you will surely have these symptoms. Now, 1 in 6
million people have this disease. Let's assume that 1/3 of the population has these symptoms.
What's your chance of having the disease, given that you have the symptoms? - CORRECT
ANSWER ✔✔1 in 2 million
Sticking to our previous example, we said that the probability
p(disease | given the | symptoms) was 1/2,000,000 = 0.00005 %
What had we assumed is the probability p(symptoms | given the | disease)? - CORRECT
ANSWER ✔✔100 %
If something went viral, looking at it, there is a high probability that it has been sent by an
influencer: p(influencer | viral)
What about p(viral | influencer), the probability that something goes viral, given that it was sent
by an influencer? - CORRECT ANSWER ✔✔Low probability
The proposed model consists of the following: - CORRECT ANSWER ✔✔Take a hypothetical
network, select some nodes, and simulate a contagion process by assuming that neighboring
nodes have a fixed probability of getting infected
,The horizontal x-axis presents: - CORRECT ANSWER ✔✔If a given network (of the simulated
networks) has few or many links
What is the lesson learned here? Whether someone is influential depends on: - CORRECT
ANSWER ✔✔the general structure of the network
Even tough we cannot predict who is influential, why is it still worthwhile for companies to pay
large amounts of money to celebrities to send out messages? - CORRECT ANSWER ✔✔Because
chances are that among large number of people reached by them, some turn out to be
influential, who will then influence others
What is the difference between this lecture on Social Network Analysis, and the previous lecture
on the same topic? - CORRECT ANSWER ✔✔Today we will look into dynamically evolving
networks + start to simulate theoretical networks
Closeness centrality is calculated as: - CORRECT ANSWER ✔✔the sum of the length of the
shortest paths between the node and all other nodes in the graph
What is one common way to scientifically test whether there's something special about your
network? - CORRECT ANSWER ✔✔You create a large number of random networks, and
compare your network with it
Multiplex network: - CORRECT ANSWER ✔✔entities are connected to each other via multiple
types of connections
Look at this pseudo "theory" (on the left) and then at the "hypothesis" on the right. Can you see
how the scientific hypothesis makes an informal verbal idea more concrete? What aspects are
equivalent in this translation? (check all that apply) - CORRECT ANSWER ✔✔"who
communicate" = "communication network"
"more friend" = "higher degree of centrality"
, " have....friend" = "friendship network"
If you found that your network is not (statistically) different from the random networks you
created, what would the conclusion be? (check all that apply) - CORRECT ANSWER ✔✔It is likely
luck of the draw if I find something special in the network. I would have found it in any
randomly drawn up network of that kind.
I can claim that my network is just another random network
I cannot claim that there's anything special about my network
Let's assume a very simple network with three nodes (A, B, C) and one (undirected) link: G(n,M)
= G(3,1). How many different networks can you form with that? - CORRECT ANSWER ✔✔3
Wait! I thought you can do 3 graphs with 3 nodes and 1 link! What's the connection here? -
CORRECT ANSWER ✔✔All possible G(3,2) become all G(3,1), when exchanging the "missing
link" with the "existing links"
Wait again! What was the difference between the "numerical solution" and the "analytical
solution"? - CORRECT ANSWER ✔✔For numerical solutions, you enumerate the options and
basically count, for analytical solutions you use math to derive the results
In network analysis, a component is: - CORRECT ANSWER ✔✔a part of the network in which a
path can get you from a node to any other node
How many of the 50 people are in the "giant component" at this point (in the largest connected
subgraph)? - CORRECT ANSWER ✔✔3
answers graded A+ 2025/2026
Wait! How much do some top celebrities get paid per tweet? - CORRECT ANSWER ✔✔US$
10,000 or more
What does the "two-step flow model" say? Information flows: - CORRECT ANSWER ✔✔from the
media, to influencers, to the public
What are the two complementary aspects of Computational Social Science Prof. Lamberson
from UCLA will talk about? - CORRECT ANSWER ✔✔empirical work + computer simulations
The only truly influential people in society are celebrities and famous people, like Justin Bieber,
Barack Obama, and Kim Kardashian. - CORRECT ANSWER ✔✔False
What trick did Prob. Lamberson use in order to track who re-posted a URL-link to a story on
Twitter? - CORRECT ANSWER ✔✔He tracked short URL, which are unique to the post
What are 'Twitter cascades'? - CORRECT ANSWER ✔✔An information diffusion process on Titter
in which a number of people make the same decision of passing along information in a
sequential fashion
What is the first thing researchers found when looking at the empirical evidence about Tweets
that go viral? - CORRECT ANSWER ✔✔The vast majority of posts never get retweeted, but a
small fraction of links go viral
,Does this sound familiar? In a data science framework, what are the first and second part of the
data refer to? - CORRECT ANSWER ✔✔Training set & test set
If it turned out that one of the top-25 most retweeted URLs came from an account that had
little influence in the past, and has a small number of followers, where would it be located in
this graph? - CORRECT ANSWER ✔✔Bottom left
If it turned out that one of the top-25 most retweeted URLs came from an account that had
MID-LEVEL influence in the past, and has a small number of followers, where would it be
located in this graph? - CORRECT ANSWER ✔✔Mid-bottom
Let's assume that if you have this disease, you will surely have these symptoms. Now, 1 in 6
million people have this disease. Let's assume that 1/3 of the population has these symptoms.
What's your chance of having the disease, given that you have the symptoms? - CORRECT
ANSWER ✔✔1 in 2 million
Sticking to our previous example, we said that the probability
p(disease | given the | symptoms) was 1/2,000,000 = 0.00005 %
What had we assumed is the probability p(symptoms | given the | disease)? - CORRECT
ANSWER ✔✔100 %
If something went viral, looking at it, there is a high probability that it has been sent by an
influencer: p(influencer | viral)
What about p(viral | influencer), the probability that something goes viral, given that it was sent
by an influencer? - CORRECT ANSWER ✔✔Low probability
The proposed model consists of the following: - CORRECT ANSWER ✔✔Take a hypothetical
network, select some nodes, and simulate a contagion process by assuming that neighboring
nodes have a fixed probability of getting infected
,The horizontal x-axis presents: - CORRECT ANSWER ✔✔If a given network (of the simulated
networks) has few or many links
What is the lesson learned here? Whether someone is influential depends on: - CORRECT
ANSWER ✔✔the general structure of the network
Even tough we cannot predict who is influential, why is it still worthwhile for companies to pay
large amounts of money to celebrities to send out messages? - CORRECT ANSWER ✔✔Because
chances are that among large number of people reached by them, some turn out to be
influential, who will then influence others
What is the difference between this lecture on Social Network Analysis, and the previous lecture
on the same topic? - CORRECT ANSWER ✔✔Today we will look into dynamically evolving
networks + start to simulate theoretical networks
Closeness centrality is calculated as: - CORRECT ANSWER ✔✔the sum of the length of the
shortest paths between the node and all other nodes in the graph
What is one common way to scientifically test whether there's something special about your
network? - CORRECT ANSWER ✔✔You create a large number of random networks, and
compare your network with it
Multiplex network: - CORRECT ANSWER ✔✔entities are connected to each other via multiple
types of connections
Look at this pseudo "theory" (on the left) and then at the "hypothesis" on the right. Can you see
how the scientific hypothesis makes an informal verbal idea more concrete? What aspects are
equivalent in this translation? (check all that apply) - CORRECT ANSWER ✔✔"who
communicate" = "communication network"
"more friend" = "higher degree of centrality"
, " have....friend" = "friendship network"
If you found that your network is not (statistically) different from the random networks you
created, what would the conclusion be? (check all that apply) - CORRECT ANSWER ✔✔It is likely
luck of the draw if I find something special in the network. I would have found it in any
randomly drawn up network of that kind.
I can claim that my network is just another random network
I cannot claim that there's anything special about my network
Let's assume a very simple network with three nodes (A, B, C) and one (undirected) link: G(n,M)
= G(3,1). How many different networks can you form with that? - CORRECT ANSWER ✔✔3
Wait! I thought you can do 3 graphs with 3 nodes and 1 link! What's the connection here? -
CORRECT ANSWER ✔✔All possible G(3,2) become all G(3,1), when exchanging the "missing
link" with the "existing links"
Wait again! What was the difference between the "numerical solution" and the "analytical
solution"? - CORRECT ANSWER ✔✔For numerical solutions, you enumerate the options and
basically count, for analytical solutions you use math to derive the results
In network analysis, a component is: - CORRECT ANSWER ✔✔a part of the network in which a
path can get you from a node to any other node
How many of the 50 people are in the "giant component" at this point (in the largest connected
subgraph)? - CORRECT ANSWER ✔✔3
