AERA to Offer Course on Text Classification with Qualitative Evidence on July 11—Register Now
AERA to Offer Course on Text Classification with Qualitative Evidence on July 11—Register Now
 
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June 2023

The 2023 AERA Virtual Research Learning Series continues with another course on July 11. Manuel S. Gonzalez Canche (University of Pennsylvania) will lead “Text Classification for the Pursuit of Truth with Qualitative Evidence: No-Code Machine Learning Via Latent Code Identification.”

Labeling or classifying textual data is an expensive and consequential challenge for mixed-methods and qualitative researchers. The rigor and consistency behind the construction of these labels may ultimately shape research findings and conclusions. How to address this challenge is a methodological conundrum: On one hand is the need for human reasoning to create classifications that lead to deep and nuanced understandings, and on the other hand is the well-documented increase in classification inconsistencies and errors that come with manual human classification, particularly when it involves vast amounts of text and teams of coders.

This course will offer an analytic framework designed to leverage the power of machine learning to classify textual data while also leveraging the advantages of human reasoning in the classification process. This framework was designed to mirror as closely as possible the line-by-line coding employed in manual code identification, while relying instead on latent Dirichlet allocation, text mining, MCMC, Gibbs sampling, and advanced data retrieval and visualization. A set of analytic output provides complete transparency of the classification process and aids to recreate the contextualized meanings embedded in the original texts.

Prior to the course, participants are encouraged to read two articles to prepare. The articles are accessible here.

This course is the third in the six-course 2023 AERA Virtual Research Learning Series, which will run through September. Course descriptions and registration information are available on the AERA website. All courses will provide dynamic instruction with active discussion, access to course materials, and Q&A with participants.

The cost of each course is $40 for AERA members and $55 for non-members. Registration includes not only the four-hour real-time class experience but also continued on-demand access to the recorded course through the AERA Virtual Research Learning Center.

Questions about the courses can be directed to profdevel@aera.net.