Call for Papers: Big Data and Behavior Science

Big Data and Behavior Science: Advanced Quantitative and Computational Techniques for Analyzing Behavior Data

Submission Deadline: June 1, 2022

Guest Associate Editors:

David J. Cox, Ph.D., M.S.B., BCBA-D, Behavioral Health Center of Excellence; Endicott College
Michael Young, Ph.D., Kansas State University
Slobodan Vucetic, Ph.D., Temple University

Data science refers to the use of advanced statistics, applied mathematics, and computational techniques to study or understand some domain of interest – often by leveraging large data sets. Recent advances in data science techniques and implementation have made data science methods increasingly accessible to behavioral researchers. Given the large amounts of data collected on research participants in many behavioral studies, we invite the submission of scholarly work for how behavior scientists are leveraging large data sets and data science techniques to study behavior. Examples of such advanced techniques include nonlinear modeling, splines, machine learning, LCA/LPA/cluster analysis, ordinal statistics, time series analyses, web scraping, and natural language processing. Manuscripts can represent tutorials, example applications, or literature reviews for how behavior scientists can or are leveraging these techniques. 

To be included in the special section, papers should be submitted by June 1, 2022. When submitting, identify your manuscript use the drop-down menu to indicate that this is intended to be part of the Special Section on Big Data and Behavior Science.