Methods 101: What is machine learning, and how does it work?
We explain the basics of machine learning – using computer programs to identify patterns in data – and how it allows researchers at the Center to analyze data on a large scale.
For Global Legislators on Twitter, an Engaged Minority Creates Outsize Share of Content
Although most national officials use the platform, their posts receive only a small number of likes and retweets.
Black imprisonment rate in the U.S. has fallen by a third since 2006
There were 1,501 black prisoners for every 100,000 black adults in 2018, down sharply from 2,261 black inmates per 100,000 black adults in 2006.
Few U.S. sermons mention abortion, though discussion varies by religious affiliation and congregation size
Roughly one-in-five of the Christian congregations we analyzed in an eight-week period heard at least one sermon that mentioned abortion.
Nigerians living near a major Belt and Road project grew more positive toward China after it was completed
Our analysis assesses the relationship between Nigerians’ distance to a major Chinese investment in their country and their views toward China.
Tweets by members of Congress tell the story of an escalating COVID-19 crisis
More than half of all tweets sent by members of the U.S. Congress between March 11 and 21 were related to the coronavirus outbreak.
How Americans feel about the satisfactions and stresses of modern life
Most Americans are at least somewhat happy with their lives, but some have grappled with issues like loneliness and work-life balance.
Democrats on Twitter more liberal, less focused on compromise than those not on the platform
A 56% majority of Democrats and Democratic-leaning independents who use Twitter describe their political views as liberal or very liberal.
U.S. churchgoers are satisfied with the sermons they hear, though content varies by religious tradition
There are differences by religious tradition in how satisfied churchgoers are with what they hear from the pulpit.
Q&A: Why we studied American sermons and how we did it
Dennis Quinn, computational social scientist, explains how our analysis of sermons came together and the challenges that arise when religion meets big data.
