About the Journal

Aims and Scope

The Journal of Behavioral Data Science is an international, peer-reviewed, open-access journal that provides a free-to-publish platform for high-quality, original research from researchers and practitioners in the field of data science and data analytics. The journal's mission is to promote interdisciplinary collaboration and the dissemination of innovative research in behavioral data science. While the journal covers a broad range of topics in data science and analysis, we categorize it into seven non-mutually exclusive sections.

  1. Theory and Methods: This section publishes articles on the development of new mathematical and statistical techniques and methods for data analysis.

  2. Application and Case Studies: This section highlights the application of data analysis techniques to specific data in social, behavioral, education, physical, biological sciences, and related areas to deepen our understanding of phenomena in one or more disciplines.

  3. Tutorials: This section publishes papers that provide step-by-step explanations of how to apply a particular method or technique.

  4. Algorithms: This section publishes papers that present new algorithms to improve the efficiency of existing methods and techniques.

  5. Software: This section publishes papers on data analysis software and programs, such as R functions, R packages, SAS macros, or stand-alone programs.

  6. Data sets: This section publishes original data sets collected for use in research and analysis.

  7. Book and Software Reviews: This section publishes reviews of books and software relevant to the field of behavioral data science.

By covering a diverse range of topics, the journal aims to facilitate interdisciplinary collaboration and innovation in the field of behavioral data science.