Abstract

Adolescent use of social media continues to evolve as new modes of communication, platforms, and ways to connect globally expand. Major social media platforms have implemented strategies to help remove and reduce the spread of dangerous content. However, these strategies are not universally effective, continuing to allow dangerous, false, and misleading information to spread across many online platforms. This study utilizes a mixed methods approach, bridging thematic analysis with computational approaches using machine learning and natural language processing, to identify areas of opportunity to engage users, reduce restrictions on free speech/exchange of ideas, and identify clinical areas of opportunity in the ED population.

Full Text
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