Examining Analytic Practices in Latent Dirichlet Allocation Within Psychological Science: Scoping Review.

ABSTRACT:

Background

Topic modeling approaches allow researchers to analyze and represent written texts. One of the commonly used approaches in psychology is latent Dirichlet allocation (LDA), which is used for rapidly synthesizing patterns of text within "big data," but outputs can be sensitive to decisions made during the analytic pipeline and may not be suitable for certain scenarios such as short texts, and we highlight resources for alternative approaches. This review focuses on the complex analytical practices specific to LDA, which existing practical guides for training LDA models have not addressed.

Objective

This scoping review used key analytical steps (data selection, data preprocessing, and data analysis) as a framework to understand the methodological approaches being use

SUBMITTER: Hagg LJ 

PROVIDER: S-EPMC9682457 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature