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

被引：0
|
作者：
Qi Zhou
Yuling Lei
Hang Du
Yuexian Tao
机构：
[1] Hangzhou Normal University,
来源：
Scientific Reports | / 13卷
关键词：
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
引用
收藏
相关论文
共 50 条
  • [21] Morse Recognition Algorithm Based on K-means
    Qu Shanhu
    Liu Hongbo
    Zhang Xu
    2019 CROSS STRAIT QUAD-REGIONAL RADIO SCIENCE AND WIRELESS TECHNOLOGY CONFERENCE (CSQRWC), 2019,
  • [22] Analyzing the Evolution of Rare Events via Social Media Data and k-means Clustering Algorithm
    Lu, Xiaoyu Sean
    Z, Mengchu
    2016 IEEE 13TH INTERNATIONAL CONFERENCE ON NETWORKING, SENSING, AND CONTROL (ICNSC), 2016,
  • [23] Learning Collective Behavior of Social Media Sites using Variant of k-means Algorithm.
    Minal, Magare G.
    Patil, D. R.
    2015 INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING (ICPC), 2015,
  • [24] Analyzing the Evolution of Rare Events via Social Media Data and k-means Clustering Algorithm
    Lu, Xiaoyu Sean
    Zhou, MengChu
    2016 IEEE 13TH INTERNATIONAL CONFERENCE ON NETWORKING, SENSING, AND CONTROL (ICNSC), 2016,
  • [25] Social Media Analysis using Optimized K-Means Clustering
    Alsayat, Ahmed
    El-Sayed, Hoda
    2016 IEEE/ACIS 14TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING RESEARCH, MANAGEMENT AND APPLICATIONS (SERA), 2016, : 61 - 66
  • [26] Modulation Decoding Based on K-Means Algorithm for Bit-Patterned Media Recording
    Jeong, Seongkwon
    Lee, Jaejin
    APPLIED SCIENCES-BASEL, 2022, 12 (17):
  • [27] Research on Characteristics of Chinese Herbal Medicine Compounds Based on Bisecting k-Means Algorithm
    Wu, Yushu
    Xie, Fenfen
    Wang, Lu
    Zhang, Shoude
    Zhang, Lei
    Wang, Xiaoying
    FUZZY SYSTEMS AND DATA MINING VI, 2020, 331 : 351 - 359
  • [28] Public attitudes towards social media field experiments
    Straub, Vincent J.
    Burton, Jason W.
    Geers, Michael
    Lorenz-Spreen, Philipp
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [29] An Alert Aggregation Algorithm Based on K-means and Genetic Algorithm
    Lu, Xianguang
    Du, Xuehui
    Wang, Wenjuan
    2018 2ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE APPLICATIONS AND TECHNOLOGIES (AIAAT 2018), 2018, 435
  • [30] A Clustering K-means Algorithm Based on Improved PSO Algorithm
    Tan, Long
    2015 FIFTH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS AND NETWORK TECHNOLOGIES (CSNT2015), 2015, : 940 - 944
12345