Abstract
Latent Dirichlet allocation (LDA) topic models are increasingly being used in communication research. Yet, questions regarding reliability and validity of the approach have received little attention thus far. In applying LDA to textual data, researchers need to tackle at least four major challenges that affect these criteria: (a) appropriate pre-processing of the text collection; (b) adequate selection of model parameters, including the number of topics to be generated; (c) evaluation of the model’s reliability; and (d) the process of validly interpreting the resulting topics. We review the research literature dealing with these questions and propose a methodology that approaches these challenges. Our overall goal is to make LDA topic modeling more accessible to communication researchers and to ensure compliance with disciplinary standards. Consequently, we develop a brief hands-on user guide for applying LDA topic …
| Original language | English |
|---|---|
| Title of host publication | Computational methods for communication science |
| Editors | Wouter Van Atteveldt, Tai-Quan Peng |
| Publisher | Routledge |
| Pages | 13-38 |
| Number of pages | 25 |
| ISBN (Print) | 987-0-367-53616-9 |
| DOIs | |
| Publication status | Published - 29 Mar 2021 |
Austrian Fields of Science 2012
- 508007 Communication science
- 508009 Media research
Keywords
- Content analysis
- Communication research methods
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