What does big data offer for computational social science
Module 1 Quiz >>> What does big data offer for computational social science >>> Big Data, Artificial Intelligence, and Ethics
1.
Question 1
What does big data offer for computational social science?
1 / 1 point
Computer simulations
Integrated induction
Theoretical analysis
==========================================
3.
Question 3
When we try to integrate messy data from different sources and see the big picture from it, this aspect of big data is known as:
1 / 1 point
Real-time fusion
No sampling
Data-fusion
Digital footprint
==========================================
5.
Question 5
Why did machine learning become so effective after we had ‘big data’?
1 / 1 point
Companies had the funds to invent it
A series of serendipitous coincidences
National Security Agencies had the funds to invent it
Massive data allowed machines to learn from data
==========================================
2.
Question 2
In lecture, we identified a list of several characteristics of “big data”. Which one was NOT part of our characterization?
1 / 1 point
Data is so comprehensive and well-organized that one single source is enough
Recorded observations are often readily and abundantly available
We work with complementary data sources and patch them together
Machine intelligence is often the only way to help us analyzing the data
==========================================
4.
Question 4
More than 2 out of 7 (some 30%) of people on Earth are on Facebook. Therefore, Facebook gives a very representative sample of the human population.
1 / 1 point
True
False
For example, Facebook is notoriously skewed with regards to age. It doesn’t represent all people from all age groups equally well.
==========================================
5.
Question 5
What was the main catalyzer to give machine learning the dominant role it has nowadays?
1 / 1 point
Massive amounts of data to train algorithms
National Security Agencies had the funds to invent it
A series of serendipitous coincidences
Companies had the funds to invent it
==========================================
6.
Question 6
Sometimes, in the industry, ‘big data’ is characterized by ‘the four Vs’. Which one is NOT one of them:
1 / 1 point
Verifiability
Variety
Volume
Velocity
==========================================
7.
Question 7
As early as in the 2012 Presidential campaign, the Obama campaign spent more money in data management projects than TV ads. Which of the following data sources did they collect to create some 16 million unique voter profiles?
1 / 1 point
Employment documents matched with household surveys
Tweets, Facebook postings, TV setup boxes
Telephone survey results matched with census data
Citizen profiles from different National Security Agencies
==========================================
4.
Question 4
While Twitter and LinkedIn are rather small social networks, Facebook and Google are representative of human kind
1 point
False
True
==========================================
7.
Question 7
As early as in the 2012 Presidential campaign, the Obama campaign spent more money in data management projects than TV ads. What was one of their main strategies, as discussed in the lecture:
1 / 1 point
Block ads from the opponent in social media like Facebook
Create fake news to reduce the credibility of the opponent
Promote selected fake news that would favor their campaign
Target different individuals with different campaign promises
2.
Question 2
In lecture, we worked with a list of several characteristics of “big data”. Which one was NOT part of our characterization?
1 point
The data is often an unavoidable byproduct of digital interaction
It often is not sampled, but it is still representative of society
Different sources are often used in a complementary way
Machine learning is often the only way we have to make sense of it