Hot Topics in Research Methods: Big Data Analysis

Welcome to the Sage Research Methods Hot Topics page, tied in this edition to the theme of big data analysis. Use the links below to gain access to examples of our various content types. Past editions can be found at the  Hot Topics archive page.

Using Text Mining Methods in Social Science Research

Watch as sociologist Gabe Ignatow discusses text mining and its applications in the social sciences. Real-world examples, resources, and advice are found in this video from Sage's data science and digital methods collection.

'Big Social Science': Doing Big Data in the Social Sciences

Learn about the emergence of a big data approach to social science, as a result of human life becoming ever more quantifiable. In this chapter of the Sage Handbook of Online Research Methods, Jonathan Bright lays out the basic practicalities of large-scale quantitative research and considers its challenges for social scientists.

Gary King on Big Data Analysis

Listen as Gary King, director of Harvard's Institute for Quantitative Social Science, considers the ever-expanding universe of data being generated and captured from daily life activities. He shares experiences from his work studying Chinese censorship of social media and shines light on the changing arenas of political action in an age of data revolution.

Big Data and Financial Crime Research: Methodological Problems

Read about the experience of conducting primary research on a quarter-century of financial crimes activity. Readers will learn of the obstacles and complexities faced by the author when deciding how to code raw data drawn from multiple sources, including tribunal hearings held in multiple languages.

Learn About Logistic Regression in R

Use this interactive dataset—a subset of data from the 2012 Cooperative Congressional National Election Study—to learn the method of logistic regression with the software program R. Logistic regression, or logit, is a widely used method of analysis in social science and is the foundation for more complex methods in big data analytics.

Readers will find a complete introduction to logistic regression with a teaching guide, student guide, and how-to guide for R, alongside a downloadable dataset, codebook, and script files for R and other common software packages.

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