Sharing the code we used to study the public’s interest in the Flint water crisis
In 2017, Pew Research Center published an analysis of Google search trends related to the water crisis in Flint, Michigan. The analysis…
A behind-the-scenes blog about research methods at Pew Research Center.
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Data Science
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Q&A: What works and what doesn’t when studying social media data
Ever since Friendster and Myspace gained popularity in the early 2000s, social scientists have been interested in studying the impact of…
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Using supervised machine learning to quantify political rhetoric
Several posts on this blog have examined unsupervised methods of natural language processing. These algorithms and models can help…
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Making sense of topic models
Topic models can produce clusters of words that characterize written documents. But how do we figure out what those clusters mean, exactly?
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An intro to topic models for text analysis
Topic models can scan documents, examine words and phrases within them, and “learn” groups of words that characterize those documents.
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Detecting subjectivity and tone with automated text analysis tools
There are a variety of tools that can help researchers analyze large volumes of written material. In this post, I’ll examine two of these…
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Using APIs to collect website data
At Pew Research Center, we regularly use APIs to collect information for the studies we produce. Web APIs provide a means of communication between websites and users, structured by rules.
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Welcome to Decoded!
An introduction to the methodological musings, puzzles and tangles that you would see if you could flip those picture-perfect research products over.
