Accepted for/Published in: JMIR Dermatology
Date Submitted: Apr 5, 2021
Date Accepted: Aug 5, 2021
Date Submitted to PubMed: Aug 26, 2023
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Identifying and intercepting health misinformation on Reddit dermatology forums with artificially intelligent bots using natural language processing
ABSTRACT
Background:
Reddit, the fifth most popular website in the United States, boasts a large and engaged user base on its dermatology forums where users crowdsource free medical opinions. Unfortunately, much of the advice provided is unvalidated and could lead to inappropriate care. Initial testing has shown that artificially intelligent bots can detect misinformation on Reddit forums and may be able to produce responses to posts containing misinformation.
Objective:
To analyze the ability of bots to find and respond to health misinformation on Reddit’s dermatology forums in a controlled test environment.
Methods:
Using natural language processing techniques, we trained bots to target misinformation using relevant keywords and to post pre-fabricated responses. By evaluating different model architectures across a held-out test set, we compared performances.
Results:
Our models yielded data test accuracies ranging from 95%-100%, with a BERT fine-tuned model resulting in the highest level of test accuracy. Bots were then able to post corrective pre-fabricated responses to misinformation.
Conclusions:
Using a limited data set, bots had near-perfect ability to detect these examples of health misinformation within Reddit dermatology forums. Given that these bots can then post pre-fabricated responses, this technique may allow for interception of misinformation. Providing correct information, even instantly, however, does not mean users will be receptive or find such interventions persuasive. Further work should investigate this strategy’s effectiveness to inform future deployment of bots as a technique in combating health misinformation. Clinical Trial: N/A
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