Understanding the Language of ADHD and Autism Communities on Social Media.

Niloofar Kalantari, Amirreza Payandeh,Marcos Zampieri, Vivian Genaro Motti

2023 IEEE International Conference on Big Data (BigData)（2023）

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摘要

Health communities online are popular for individuals to discuss health challenges and exchange social support. With social media, online communities also benefit neurodivergent individuals, by creating inclusive spaces where sharing of experience and knowledge is encouraged. The discussion in online communities covers a wide range of topics. As a result, the discussions differ in terms of topics, tone, and approach. This paper presents an analysis of social media posts shared on Reddit communities on Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorders (ASD) between 2018 and 2020. In the study, we use a computer-aided model to identify prevalent topics in each subreddit and common themes. We conduct a comparative analysis of the communities and assess theme frequency and sentiment. The study highlights common topics found in r/adhd and r/autism subreddits, including diagnosis, treatment (medication dose and side effects), and social aspects (school, work, and peer interactions).

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关键词

Social Media,Attention Deficit Hyperactivity Disorder,Autism Community,Side Effects,Social Aspects,Online Communities,Social Media Data,Peer Interactions,Neurodiversity,Mental Health,Social Interaction,Large Datasets,Qualitative Methods,Social Media Platforms,Impulsivity,Medical Advice,Topic Modeling,Word Embedding,Sentiment Analysis,Family Dynamics,Latent Dirichlet Allocation,Positive Sentiment,Coherence Score,Social Media Channels,Model Of Autism,Latent Dirichlet Allocation Model,Negative Sentiment,Gibbs Sampling,Pairs Of Subjects

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