Download Report IEEE DataPort : Chinese Social Media Autism Children Dataset (CSMACD) - 2025
CSV, TXT by Wondimagegn Bekele Munto, Mengying Zhou, Wei Li, Zhihai Lv, Na Li, Yuanjie Cao, Yi Pan, Sufen Hu, Yanjie Wei, Wenhui Xi
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Format: CSV, TXT Publisher: IEEE DataPort Publication Date of the Electronic Edition: 11/12/2025
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ISBN: 10.21227/7hqx-me42
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Description
This paper introduces the Chinese Social Media Autism Children Dataset (CSMACD), a novel resource for autism spectrum disorder (ASD) research. CSMACD compiles high-definition, unobstructed frontal facial images of Chinese children (aged 6 months to 15 years) with ASD, sourced from mainstream social media platforms (e.g., Bilibili, Douyin, and Tencent Video). Videos were identified using ASD-related keywords (e.g., "autism," "Star Baby") and recommendation algorithms. A total of 182 ASD facial images (140 males, 42 females) were curated by verifying uploader claims and analyzing video content. To establish a neurotypical (TD) control group, 182 pediatric facial images with matched gender ratios were manually selected from the East Asian subset of the Flickr-Faces-HQ Dataset (FFHQ). All data, including video links and facial landmarks, are publicly available via GitHub and Gitee repositories. While CSMACD is designed to expand with future social media contributions, its open-source nature necessitates caution due to potential variability in label accuracy and data quality. This dataset aims to support research in ASD facial analysis, machine learning, and cross-cultural behavioral studies.
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