Are topic models reliable or useful?
The final post in our series examines how topic models can and can’t help when classifying large amounts of text.
A behind-the-scenes blog about research methods at Pew Research Center.
For our latest findings, visit pewresearch.org.
The final post in our series examines how topic models can and can’t help when classifying large amounts of text.
Keyword oversampling can be a powerful way to analyze uncommon subsets of text data.
The Pareto principle, or “80/20 rule,” holds that in many systems, a minority of cases produce the majority of outcomes.
In a recent project involving focus groups, we tested out quantitative as well as qualitative research methods.
We’re excited to release a collection of Python tools that we’ve found ourselves returning to again and again.
Three widely cited coronavirus trackers differ in their methods and in the kinds of information they provide.
It can be hard to determine whether parties near the ends of the ideology scale are more popular on the platform than moderate parties.
Understanding the exact meaning of a set of words requires an intimate understanding of how the words are used in your data and the meaning they’re likely intended to convey in context.
Overall, our survey found that 13% of U.S. adult Twitter users keep their feeds private.
Survey researchers frequently explore differences in public opinion by demographic group — how men’s views compare with those of women, for example, or how younger people compare with older people. Often, it’s also possible to look at differences by survey respondents’ geographic location. Yet, when geographic information is available in survey data, it’s not always […]