了解自闭症情绪动态 社交媒体社区 社交媒体社区
Elia Gabarron1,2, Enrique Dorronzoro3, Octavio Rivera-Romero3
1Department of Education, ICT and Learning, Østfold University College, Norway.
Studies in health technology and informatics
|August 23, 2024
概括
关于自闭症的社交媒体帖子揭示了不同的情绪色调. 标签#ActuallyAutistic与少的快乐和更多的悲伤相关,强调需要为自闭症社区提供更多支持.
科学领域:
- 社交媒体分析
- 计算语言学计算语言学
- 自闭症研究的研究.
背景情况:
- 社交媒体平台越来越多地被用来讨论自闭症,为社区体验提供了洞察力.
- 情绪分析提供了一个细微的理解特定的情绪状态超越一般的情绪分析.
研究的目的:
- 识别和比较社交媒体关于自闭症的帖子中表达的情绪.
- 专门分析帖子中的情绪,使用#ActuallyAutistic标签对比那些没有.
主要方法:
- 提取了大量与自闭症相关的社交媒体帖子样本.
- 使用DistilBERT,一种机器学习模型,用于情绪分类.
- 给每个帖子分配六种情绪之一 (悲伤,快乐,爱,愤怒,恐惧,惊喜).
主要成果:
- 分析了414,287条帖子; 23.8%使用了#ActuallyAutistic.
- 快乐是最常见的情绪 (52.5%),其次是悲伤 (28.6%).
- #ActuallyAutistic的帖子显示,与其他帖子相比,快乐程度显著降低 (27.1%),悲伤程度更高 (52.7%).
结论:
- #ActuallyAutistic标签与一个独特的情感特征联系在一起:欢乐减少,悲伤增加.
- 调查结果强调需要加强对自闭症社区在线和离线的支持和接受.
- 结果可以为旨在改善自闭症个体福祉和包容性的政策和计划提供信息.
相关概念视频
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