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.
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Data Availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Notes
NB: We set the x-axis maximum value to 25,000 words for this figure to allow the reader to more easily see the distributions across journals. Trimming the x-axis to 25,000 words, however, removed 10 data points from JEAB with word counts of 39,116; 37,519; 36,476; 32,592; 31,170; 28,415; 28,341; 28,112; 27,850; and 27,090.
We thank an anonymous reviewer for highlighting many of these.
We thank an anonymous reviewer for highlighting this pattern in our dataset.
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Sosine, J., Cox, D.J. Identifying Trends in the Open-Access Behavior Analytic Literature via Computational Analyses (I): Simple Descriptions of Text. Analysis Verbal Behav 39, 146–167 (2023). https://doi.org/10.1007/s40616-022-00179-4
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DOI: https://doi.org/10.1007/s40616-022-00179-4