Public concerns and attitudes towards autism on Chinese social media based on K-means algorithm

To investigate the hot topics and attitudes of autism in the larger community. In this study, we analyzed and summarized experimental texts from the social media platform Zhihu using the TF-IDF algorithm and K-means clustering approach. Based on the analysis of the 1,740,826-word experimental text,...

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Detalles Bibliográficos
Autores principales: Zhou, Qi, Lei, Yuling, Du, Hang, Tao, Yuexian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10499991/
https://www.ncbi.nlm.nih.gov/pubmed/37704712
http://dx.doi.org/10.1038/s41598-023-42396-4
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author Zhou, Qi
Lei, Yuling
Du, Hang
Tao, Yuexian
author_facet Zhou, Qi
Lei, Yuling
Du, Hang
Tao, Yuexian
author_sort Zhou, Qi
collection PubMed
description To investigate the hot topics and attitudes of autism in the larger community. In this study, we analyzed and summarized experimental texts from the social media platform Zhihu using the TF-IDF algorithm and K-means clustering approach. Based on the analysis of the 1,740,826-word experimental text, we found that the popularity of autism has steadily risen over recent years. Sufferers and their parents primarily discuss autism. The K-means clustering algorithm revealed that the most popular topics are divided into four categories: self-experience of individuals with autism, external views of individuals with autism, caring and stressful behaviors of caregivers, and information about autism. This study concluded that people with autism face more incredible negative emotions, external cognitive evaluations of the autistic group reflect stereotypes, the caregiver’s family suffers high financial and psychological stress, and disorders caused by disease in autistic individuals.
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spelling pubmed-104999912023-09-15 Public concerns and attitudes towards autism on Chinese social media based on K-means algorithm Zhou, Qi Lei, Yuling Du, Hang Tao, Yuexian Sci Rep Article To investigate the hot topics and attitudes of autism in the larger community. In this study, we analyzed and summarized experimental texts from the social media platform Zhihu using the TF-IDF algorithm and K-means clustering approach. Based on the analysis of the 1,740,826-word experimental text, we found that the popularity of autism has steadily risen over recent years. Sufferers and their parents primarily discuss autism. The K-means clustering algorithm revealed that the most popular topics are divided into four categories: self-experience of individuals with autism, external views of individuals with autism, caring and stressful behaviors of caregivers, and information about autism. This study concluded that people with autism face more incredible negative emotions, external cognitive evaluations of the autistic group reflect stereotypes, the caregiver’s family suffers high financial and psychological stress, and disorders caused by disease in autistic individuals. Nature Publishing Group UK 2023-09-13 /pmc/articles/PMC10499991/ /pubmed/37704712 http://dx.doi.org/10.1038/s41598-023-42396-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Zhou, Qi
Lei, Yuling
Du, Hang
Tao, Yuexian
Public concerns and attitudes towards autism on Chinese social media based on K-means algorithm
title Public concerns and attitudes towards autism on Chinese social media based on K-means algorithm
title_full Public concerns and attitudes towards autism on Chinese social media based on K-means algorithm
title_fullStr Public concerns and attitudes towards autism on Chinese social media based on K-means algorithm
title_full_unstemmed Public concerns and attitudes towards autism on Chinese social media based on K-means algorithm
title_short Public concerns and attitudes towards autism on Chinese social media based on K-means algorithm
title_sort public concerns and attitudes towards autism on chinese social media based on k-means algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10499991/
https://www.ncbi.nlm.nih.gov/pubmed/37704712
http://dx.doi.org/10.1038/s41598-023-42396-4
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