In their study titled "Beyond standardization: a comprehensive review of topic modeling validation methods for computational social science research," Jana Bernhard-Harrer, Randa Ashour, Jakob-Moritz Eberl, Petro Tolochko, and Hajo Boomgaarden provide a systematic review of topic modeling validation practices in computational social science research.

As computational text analysis becomes increasingly popular in the social sciences, topic modeling has emerged as a widely used method for uncovering latent themes in textual data. However, concerns about the validity of topic modeling results have persisted, particularly due to the lack of standardized validation practices. This study addresses these concerns by systematically reviewing 789 studies that employ topic modeling, investigating whether the field is moving toward a common framework for validation.

The findings reveal a significant gap in standardized validation practices and a lack of convergence toward specific methods. The authors argue that this gap stems from the tension between the inductive, qualitative nature of topic modeling and the deductive, quantitative tradition that underpins standardized validation. To address this issue, the study advocates for the integration of qualitative validation approaches, emphasizing transparency and detailed reporting to enhance the credibility of findings in computational social science research.

This comprehensive review offers valuable insights for researchers using topic modeling, highlighting the need for more robust and transparent validation practices to ensure the reliability of results in this growing field.

Find the full paper here: doi:10.1017/psrm.2025.10008

Cite the article:
Bernhard-Harrer, J., Ashour, R., Eberl, J.-M., Tolochko, P., & Boomgaarden, H. (2025). Beyond standardization: a comprehensive review of topic modeling validation methods for computational social science research. Political Science Research and Methods, 1–19. doi:10.1017/psrm.2025.10008