Evidence map›Paper›PMID 42405993›Full record

ArticleJournal of autism and developmental disorders2026

Sentiment and Topic Analysis of Autism Spectrum Disorder Discussions on Chinese Social Media: Evidence From Bilibili and Rednote.

Baixue Gao, Yunlong Xie, Hongyu Li, Wen He

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Article in Journal of autism and developmental disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Baixue GaoSchool of Psychology, Shanghai Normal University, Shanghai, 200234, China.
Yunlong XieSchool of Psychology, Shanghai Normal University, Shanghai, 200234, China.
Hongyu LiBeijing InHand Networks Technology Co., Ltd., Beijing, China.
Wen HeSchool of Psychology, Shanghai Normal University, Shanghai, 200234, China. hewen@shnu.edu.cn.ORCID http://orcid.org/0000-0002-8535-1082

Funding

National Social Science Fund of China 25BSH101
6 · The paper itself

Abstract

purposeSocial media has become an important platform for Autism Spectrum Disorder (ASD) communication. This study aimed to analyze online posts and comments related to ASD on Chinese social media, focusing on the emotional tendencies and topics about ASD.

methodsThis study used Python to retrieve ASD posts and comments, including 1,563 posts and 17,908 comments on Chinese social media. We employed content analysis to categorize posts and utilized the BERTopic model alongside Kernel Density Estimation (KDE) to examine sentiment distribution and thematic clusters.

results(1) Content analysis revealed that in addition to Educational Information (44.5%), Personal Experience (25.5%), and Daily Life (23.1%), a fourth distinct category emerged in Chinese social media posts concerning ASD: Media Representation. This category captures how film, television series and novels shape public perception about ASD; (2) Sentiment analysis uncovered a stark "emotional polarization." While post content remained relatively balanced (52.8% positive), comment sections exhibited an overwhelming negative bias (66.9% negative), with sentiment scores heavily skewed toward the extreme low range (0-0.2); (3) BERTopic modeling identified four positive topics centered on family narratives, emotional support, intervention strategies and future survival planning. In contrast, the ten most prevalent negative topics emerged: half focus on conceptual controversies surrounding ASD, while the remainder address caregiving burdens, media criticism, and profound ethical conflicts regarding the life value of autistic individuals.

conclusionSocial media in China plays an important role in public education regarding the conceptual understanding of ASD. However, these platforms provide limited emotional and informational support for affected families, while also perpetuating negative narratives and stereotypes that contribute to the stigmatization of ASD.

Indexed as

Autism spectrum disorderBERTopicSentiment analysisSocial media

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.