CMN 150V FINAL EXAM QUESTIONS WITH
VERIFIED ANSWERS
Wait! How much do some top celebrities get paid per tweet?
US$ 10,000 or more
What does the "two-step flow model" say? Information flows:
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?
empirical work + computer simulations
What trick did Prob. Lamberson use in order to track who re-posted a URL-link to a story
on Twitter?
He tracked short URL, which are unique to the post
What are 'Twitter cascades'?
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?
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?
Training set & test set
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?
Low probability
What is the lesson learned here? Whether someone is influential depends on:
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?
, Because chances are that among large number of people reached by them, some turn out to be
influential, who will then influence others
Closeness centrality is calculated as:
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?
You create a large number of random networks, and compare your network with it
Multiplex network:
entities are connected to each other via multiple types of connections
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)
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?
3
Wait again! What was the difference between the "numerical solution" and the "analytical
solution"?
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:
a part of the network in which a path can get you from a node to any other node
Why do you need at least 1 connection per node in order for the giant component to
dominate?
everybody can have one friend (on average), making a chain of friends
In network analysis, a cycle is:
a walk that ends where it began
Who will accumulate more links over time?
VERIFIED ANSWERS
Wait! How much do some top celebrities get paid per tweet?
US$ 10,000 or more
What does the "two-step flow model" say? Information flows:
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?
empirical work + computer simulations
What trick did Prob. Lamberson use in order to track who re-posted a URL-link to a story
on Twitter?
He tracked short URL, which are unique to the post
What are 'Twitter cascades'?
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?
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?
Training set & test set
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?
Low probability
What is the lesson learned here? Whether someone is influential depends on:
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?
, Because chances are that among large number of people reached by them, some turn out to be
influential, who will then influence others
Closeness centrality is calculated as:
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?
You create a large number of random networks, and compare your network with it
Multiplex network:
entities are connected to each other via multiple types of connections
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)
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?
3
Wait again! What was the difference between the "numerical solution" and the "analytical
solution"?
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:
a part of the network in which a path can get you from a node to any other node
Why do you need at least 1 connection per node in order for the giant component to
dominate?
everybody can have one friend (on average), making a chain of friends
In network analysis, a cycle is:
a walk that ends where it began
Who will accumulate more links over time?
