Artificial Intelligence and Social Media for the Detection of Eating Disorders

  • Jinbo He*
  • , Feng Ji*
  • *Corresponding author for this work

Research output: Contribution to journalComment/debate

Abstract

Artificial intelligence (AI) has been increasingly recognized for its potential in mental health management, including detecting, preventing, and treating eating disorders (EDs). Linardon et al. investigated current practices and perspectives on AI in ED treatment from professionals and community participants. While their work provides valuable insights into AI's role in ED management in the treatment phase, the applications of AI at earlier stages, particularly for case detection, and perspectives of key groups involved in this early-stage implementation (e.g., health professionals and individuals with or at risk of EDs) remain underexplored. Given the large volume of multimodal data available on social media platforms, together with their widespread use and accessibility, the integration of AI and social media provides an ideal opportunity for conducting large-scale, population-based detection for EDs. Thus, in this commentary, we discuss AI's potential to leverage social media data for case detection, highlight related ethical considerations (e.g., bias and data privacy), and propose future research directions.

Original languageEnglish
Pages (from-to)1187-1190
Number of pages4
JournalInternational Journal of Eating Disorders
Volume58
Issue number7
DOIs
Publication statusPublished - Jul 2025
Externally publishedYes

Keywords

  • artificial intelligence
  • detection
  • eating disorders
  • social media

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