Topic Modeling of Social Media Discourse of Autism Support Groups

自闭症互助小组社交媒体话语的主题建模

阅读:1

Abstract

Social media platforms serve as critical channels for autism support groups to communicate and seek assistance. This study employed Latent Dirichlet Allocation (LDA) topic modeling to analyze discourse patterns within the Autism Bar on Baidu Tieba, a major Chinese social media. A dataset of 14,151 posts was collected through web crawling, with 12,667 posts retained after preprocessing. The analysis revealed two key findings: (1) The discourse among autism support communities on Baidu Tieba focuses on four central themes: intervention and therapy, early educational journey, early symptom detection and family interaction, and access to educational resources and community support. (2) Sociocultural factors exert a significant influence on autism-related discourse, particularly in shaping societal attitudes toward individuals with autism and the formation of support networks. Traditional Chinese cultural values, such as collectivism and familial centrality, impact the behavioral patterns and decision-making processes of families with autistic children. This study has demonstrated the unique needs and challenges faced by the autism support community, while also informing strategies to promote social media platforms as spaces for support and information exchange. The findings have practical implications for designing targeted interventions and support mechanisms for individuals with autism and their families.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。