About the Journal
ISSN: 2575-8306 (Print)
ISSN: 2574-1284 (Online)
DOI: 10.35566/jbds
The Journal of Behavioral Data Science is a peer-reviewed, open-access journal that aims to provide a free-of-charge-to-publish platform for researchers and practitioners in the area of data science and data analytics. The journal is committed to making high-quality research freely accessible to authors and readers. Publishing in the journal and accessing its content are completely free for both authors and readers. This allows for the widest possible dissemination of research, and promotes interdisciplinary collaboration and innovation in the field of behavioral data science.
In 2024, the average citation per article published in JBDS is 3.4. The average citation per article is 6.2 since its debut. See Google Scholar.
JBDS is now indexed by Scopus.
Current Issue

Moulder, R., & Tong, X. (2025). A Data Permutation Method for Testing Random Slopes of Bayesian Growth Curves. Journal of Behavioral Data Science, 5(1), 1-22. https://doi.org/10.35566/jbds/moulder
Liu, J. (2025). Extending Latent Basis Growth Model to Explore Joint Development in the Framework of Individual Measurement Occasions. Journal of Behavioral Data Science, 5(1), 1-28. https://doi.org/10.35566/jbds/jinliu
Larzelere, R., & Lin, H. (2025). An Innovation to Test Treatment X Pretest Interactions within Difference-in-Differences. Journal of Behavioral Data Science, 5(1), 51-66. https://doi.org/10.35566/jbds/larzelere
Cao, Y., Dai, J., Wang, Z., Zhang, Y., Shen, X., Liu, Y., & Tian, Y. (2025). Machine Learning Approaches for Depression Detection on Social Media: A Systematic Review of Biases and Methodological Challenges. Journal of Behavioral Data Science, 5(1), 67-102. https://doi.org/10.35566/jbds/caoyc
Bain, C., Shi, D., Banad, Y., Ethridge, L., Norris, J., & Loeffelman, J. (2025). A Tutorial on Supervised Machine Learning Variable Selection Methods in Classification for the Social and Health Sciences in R. Journal of Behavioral Data Science, 5(1), 103-147. https://doi.org/10.35566/jbds/bain
Full Issue
Theory and Methods
Literature Review
JBDS is supported by the International Society for Data Science and Analytics (ISDSA; EIN: 82-4382236), an exempt organization under section 501(c)(3) of the Internal Revenue Code. You can make a tax-deductible contribution to help the growth of JBDS.