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A new study reviews experimental research on automated journalism, revealing widespread gaps in manipulation checks, statistical power and methodological rigor

April 6, 2026

A new study finds that how researchers design automated journalism experiments—particularly their methodological choices—may be critical to better understanding how automated authors shape the psychological processing of news.

The findings were featured in “Analyzing Automated News: A Systematic Review of Experimental Evidence Across 20 Years of Research” by Frank Waddell, University of Florida College of Journalism and Communications Journalism associate professor, and Auburn University Journalism Assistant Professor Jessica Sparks, Ph.D. 2024. The article was published in Review of Communication, Volume 26, Issue 2.

The study analyzed experimental research on automated journalism to identify the common theoretical paradigms and methodological practices in published literature from 2001 to 2022. The systematic review was conducted with a focus on summarizing dominant theoretical and methodological practices including sampling, experimental manipulations, stimuli trends, measurement and data analysis.

According to the authors, “In sum, a systematic review of nearly 20 previously published experimental studies on automated news finds there is much methodological diversity across past research. There are some trends in the literature that are strengths, such as the inclusion of geographically diverse samples along with the use of validated measures and multiple news articles for heightening external validity. However, there is also room for growth, including the need for more consistent assessment of manipulation efficacy and greater justification of sample size based on effect size consideration.”

They add, “As the study of automated news continues, methodological choices may be key to providing a more comprehensive understanding of how the psychological processing of news is impacted by the proliferation of automated authors.”

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