Identifying Trends in the Open-Access Behavior Analytic Literature via Computational Analyses (I): Simple Descriptions of Text.

Abstract

Published research in scientific journals are critical resources for researchers as primary sources about: what is important in the field, the direction the field is headed, how the field relates to other sciences, and as a historical record for each of these. In this exploratory study, we analyzed the articles of five behavior analytic journals to identify trends in these areas. To do this, we downloaded all available articles (N = 10,405) since the inception of five behavior analytic journals and one control journal. We then used computational techniques to turn the collection of raw text into a structured dataset for descriptive, exploratory analyses. We found consistent differences in the length and variability of published research across behavior analytic journals compared to a control journal. We also found increasing article lengths over time which, combined with the previous finding, may highlight changing editorial contingencies that influence the writing behavior of researchers. Further, we found evidence suggesting distinct (though still connected) verbal communities between the experimental analysis of behavior and applied behavior analysis. Lastly, keyword trends suggest that increased focus on "functional analyses," "problem behavior," and "autism spectrum disorder" currently dominates the research being published in these journals similar to the practitioner arm of behavior analysis. Researchers interested in studying published behavior analytic textual stimuli will find the corresponding open dataset useful. And, for those interested in computational analyses of these data, this first pass at simple descriptions provides a launching point for much fruitful future research.

Supplementary information: The online version contains supplementary material available at 10.1007/s40616-022-00179-4.