The World of Topic Modeling in R
Bibliographic Data
| ID | 21758828 |
|---|---|
| Authors | Günter Wiedemann (0000-0002-4239-295X, Hans-Bredow-Institute, corresponding author), Gregor Wiedemann |
| Year | 2022 |
| Volume | 70 |
| Issue | 3 |
| Pages | 286-291 |
| Publication date | 2022-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Medien & Kommunikationswissenschaft (JOURNAL) |
| Journal identifiers | ISSN: 1615-634X |
| Publisher | Nomos Verlag (PUBLISHER) |
| DOI | 10.5771/1615-634x-2022-3-286 |
| OpenAlex | W4288063783 |
| Language | EN |
| Citations received | 1 |
| References cited | 8 |
This software review provides a systematic overview of R packages for topic modeling. These packages facilitate the application of computational text analysis to conduct research compatible with a wide variety of methodological frameworks employed in the social and communication sciences. For this overview, the analysis process is divided into four steps: preprocessing, inference, evaluation, and interpretation of topic models. The summary shows that the wide selection of R packages available today provides easy-to-use access to this increasingly popular computational social science method and contributes to its methodical standardization
Data science · Inference · Management science · Preprocessor · Programming language · Software engineering · Standardization · Computational and Text Analysis Methods · Computer Science · Engineering · Artificial Intelligence · Software
| Citations per year | 0.5 |
|---|---|
| Citation span | 2024 - 2024 (1) |
| Highly cited | No |