Large Language Model–Assisted Annotation Framework for Cross-Platform Analysis of Online Autism Communities: Implications for Parent Education and Digital Support - Report - MDSpire

Large Language Model–Assisted Annotation Framework for Cross-Platform Analysis of Online Autism Communities: Implications for Parent Education and Digital Support

  • By

  • Yifan Xu

  • Jianhao Ma

  • Yujia Hu

  • Yixue Liu

  • Yu Chen

  • Wei Feng

  • Changwei Zhang

  • Lei Zhang

  • Xuening Zhang

  • Ruochen Huang

  • July 10, 2026

  • 0 min

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Framework for Annotation Utilizing Large Language Models to Analyze Online Autism Communities

Overview

This study investigates the use of large language models (LLMs) to analyze online autism communities, focusing on parental education and digital support.

Background

Autism spectrum disorder (ASD) affects over 10 million individuals in China, with a significant portion being children. The management of ASD primarily involves long-term rehabilitation and psychological intervention.

Data Highlights

No specific numerical data or trial results were provided in the source material.

Key Findings

  • Over 10 million people in China are affected by autism-related disorders.
  • Approximately 20% of individuals with autism are children, with 200,000 new cases reported annually.
  • Two main types of OHCs exist: open peer forums and structured physician-patient consultation platforms.

Clinical Implications

Healthcare professionals should be aware of the role of online health communities in supporting families affected by ASD.

Conclusion

The study highlights the role of online platforms in providing support to families dealing with ASD.

Related Resources & Content

  1. Levante A, Martis C, Lecciso F, Eur J Investig Health Psychol Educ, 2025 -- The quality of the parent-child relationship in the context of autism
  2. Liu T, Hsiao RC, Chou W, Yen C, BMC Public Health, 2024 -- Parenting stress, anxiety, and sources of acquiring knowledge in Taiwanese caregivers
  3. Pillay S, Duncan M, de Vries PJ, Front Psychiatry, 2022 -- Service provider perspectives of educational services for autism spectrum disorder
  4. Chen X, PLoS One, 2023 -- Online health communities influence people's health behaviors in the context of COVID-19
  5. American Academy of Pediatrics, Pediatrics, 2025 -- Identification, Evaluation, and Management of Children With Autism Spectrum Disorder
  6. npj Digital Medicine — Utilizing Large Language Models to Enhance Diagnosis of Language Disorders Linked to Autism and Recognize Unique Characteristics
  7. npj Digital Medicine — Quantitative Evaluation of Atypical Facial Expression Patterns in Children with Autism Spectrum Disorder Through Naturalistic Interaction Dynamics
  8. Frontiers in Psychiatry — Assessing Large Language Model Responses to Pediatric Depression FAQs: A Cross-sectional Study on Readability, Accuracy, and Sentiment
  9. npj Digital Medicine — Automated AI based identification of autism spectrum disorder from home videos
  10. Utilizing Large Language Models to Enhance Diagnosis of Language Disorders Linked to Autism
  11. Quantitative Evaluation of Atypical Facial Expression Patterns in Children with Autism Spectrum Disorder
  12. Assessing Large Language Model Responses to Pediatric Depression FAQs
  13. Identification, Evaluation, and Management of Children With Autism Spectrum Disorder | Pediatrics | American Academy of Pediatrics
  14. Early Parent-Mediated Training for Social-Communication Skills in Toddlers and Preschoolers With ASD: A Systematic Review and Meta-analysis - PubMed
  15. CG170 Full guideline

Original Source(s)

Large Language Model–Assisted Annotation Framework for Cross-Platform Analysis of Online Autism Communities: Implications for Parent Education and Digital Support

  • by Yifan Xu, Jianhao Ma, Yujia Hu, Yixue Liu, Yu Chen, Wei Feng, Changwei Zhang, Lei Zhang, Xuening Zhang, Ruochen Huang

  • July 10, 2026

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