CMN 150V Final Exam – Questions With Right
Solutions
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Terms in this set (207)
How much do some top celebs get $10,000 or more
paid per tweet?
What are 2 complementary aspects of empirical work and computer simulations
computational social science
Lamberson talks about?
Are celebs the only people to have No
influence in society?
Can just anybody be influential? yes
What trick did Lamberson use in order he tracked short url, which are unique to the post
to track who reposted url link to a
story on Twitter?
What are 'Twitter Cascades'? an info diffusion process on Twitter in which a
number of people make the same decision of
passing along info in a sequential fashion
Do all posts go viral? the vast majority of posts never get retweeted, but a
small fraction of links go viral
,If something went viral, looking at it, low probability
there is a high probability that it had
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?
The proposed model consists of the take a hypothetical network, select some nodes, and
following: simulate a contagion process by assuming that
neighboring nodes have a fixed probability of
getting infected
The horizontal x-axis presents: if a given network(of simulated networks) has few or
many links
What determines what spreads or density of network
not?
Even though we cannot predict who is chances are that among the people reached by
influential, why is it worthwhile for them, some turn out to be influential, who will the
companies to pay large amounts of influence others
money to celebs to send messages?
What determines if an individual can depends much more on the global structure of the
trigger a cascade? influence network than it does on his or her personal
degree on influence
Can anyone start a cascade? the overall network permits global cascades anyone
can start one but if it doesnt then no one can
What determines if someone is depends on the general structure of the network
influential?
What is the difference between this today, we will look at dynamically evolving networks
lecture on social network analysis and and starts to simulate theoretical networks
the previous lectures on the same
topic?
, T or F? In science, things can be false
distributed in 4 diff ways: normal,
poisson, exponential, powerlaw
T or F? In science, things can be false
distributed in random, scale free,
small world, hub/spoke networks
What is one common way to you create a large number of random networks and
scientifically test whether there's compare your network with it
something special about your
network?
Let's assume a very simple network 3
with 3 nodes(A,B,C) and one
(undirected) link: G(N,M) = G(3,1). How
many different networks can you form
with that?
What was the differnece between the numerical: enumerate the options and basically
"numerical solutions" and "analytical count
solution"? analytical: 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 one everybody can have one friend (on average) making
connection per node in order for the a chain of friends
giant component to dominate?
Who will have more links? older nodes
What does preferential attachment the probability of a node to connect with new nodes
mean? corresponds to the number of existing degrees of a
node
What does preferential attachment say connects to each one of them is equally likely
in this case? The probability that a new
node:
Solutions
Save
Terms in this set (207)
How much do some top celebs get $10,000 or more
paid per tweet?
What are 2 complementary aspects of empirical work and computer simulations
computational social science
Lamberson talks about?
Are celebs the only people to have No
influence in society?
Can just anybody be influential? yes
What trick did Lamberson use in order he tracked short url, which are unique to the post
to track who reposted url link to a
story on Twitter?
What are 'Twitter Cascades'? an info diffusion process on Twitter in which a
number of people make the same decision of
passing along info in a sequential fashion
Do all posts go viral? the vast majority of posts never get retweeted, but a
small fraction of links go viral
,If something went viral, looking at it, low probability
there is a high probability that it had
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?
The proposed model consists of the take a hypothetical network, select some nodes, and
following: simulate a contagion process by assuming that
neighboring nodes have a fixed probability of
getting infected
The horizontal x-axis presents: if a given network(of simulated networks) has few or
many links
What determines what spreads or density of network
not?
Even though we cannot predict who is chances are that among the people reached by
influential, why is it worthwhile for them, some turn out to be influential, who will the
companies to pay large amounts of influence others
money to celebs to send messages?
What determines if an individual can depends much more on the global structure of the
trigger a cascade? influence network than it does on his or her personal
degree on influence
Can anyone start a cascade? the overall network permits global cascades anyone
can start one but if it doesnt then no one can
What determines if someone is depends on the general structure of the network
influential?
What is the difference between this today, we will look at dynamically evolving networks
lecture on social network analysis and and starts to simulate theoretical networks
the previous lectures on the same
topic?
, T or F? In science, things can be false
distributed in 4 diff ways: normal,
poisson, exponential, powerlaw
T or F? In science, things can be false
distributed in random, scale free,
small world, hub/spoke networks
What is one common way to you create a large number of random networks and
scientifically test whether there's compare your network with it
something special about your
network?
Let's assume a very simple network 3
with 3 nodes(A,B,C) and one
(undirected) link: G(N,M) = G(3,1). How
many different networks can you form
with that?
What was the differnece between the numerical: enumerate the options and basically
"numerical solutions" and "analytical count
solution"? analytical: 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 one everybody can have one friend (on average) making
connection per node in order for the a chain of friends
giant component to dominate?
Who will have more links? older nodes
What does preferential attachment the probability of a node to connect with new nodes
mean? corresponds to the number of existing degrees of a
node
What does preferential attachment say connects to each one of them is equally likely
in this case? The probability that a new
node:
