一个探索性的网络分析关于自闭症的讨论主题,跨越子reddit社区.
Skylar DeWitt1, Kendall Mills1, Adam M Briggs1
1Department of Psychology, Eastern Michigan University, Ypsilanti, MI 48197, USA.
Behavioral sciences (Basel, Switzerland)
|June 26, 2025
概括
机器学习分析了自闭症患者,家长和治疗师关于自闭症谱系障碍 (ASD) 的Reddit讨论. 这确定了关键的主题和模式,以改善对自闭症的支持和研究.
科学领域:
- 计算社会科学 计算社会科学
- 自闭症谱系障碍研究研究
- 机器学习应用 机器学习应用
背景情况:
- 像Reddit这样的在线社区提供了关于自闭症谱系障碍 (ASD) 经验的真实见解.
- 了解自闭症患者,家长和行为治疗师之间的讨论对于全面的支持至关重要.
研究的目的:
- 应用机器学习来识别自闭症相关Reddit讨论中的模式.
- 了解不同用户群体的关键主题,包括具有挑战性的行为评估和治疗.
主要方法:
- 使用机器学习方法的感应计算方法.
- 分析了来自自闭症个体的46,914条评论,来自家长的27,838条评论,以及来自众多子reddits的行为治疗师的3,163条评论.
- 网络分析揭示了群体内部和跨群体的讨论模式.
主要成果:
- 在自闭症患者,家长和行为治疗师之间确定了不同的和重叠的讨论主题.
- 揭示了与自闭症谱中具有挑战性的行为评估和治疗相关的模式.
- 从各组的57,46和6个子格式中提取了重要的数据.
结论:
- 机器学习可以有效地在在线自闭症讨论中发现有价值的模式.
- 结果可以为开发有针对性的支持,资源和临床实践考虑提供信息.
- 该研究强调了未来研究自闭症谱系障碍沟通和支持的途径.
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