Public Attitudes and Sentiments toward Common Prosperity in China: A Text Mining Analysis Based on Social Media

被引:0
|
作者
Li, Yang [1 ]
Duan, Tianyu [2 ]
Zhu, Lijing [2 ]
机构
[1] Cent Univ Finance & Econ, Sch Marxism, Beijing 100081, Peoples R China
[2] China Univ Petr, Sch Econ & Management, Beijing 102249, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 10期
关键词
common prosperity; sentiment analysis; text mining; topic modeling; Weibo;
D O I
10.3390/app14104295
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Since 2021, China's promotion of common prosperity has captured global attention and sparked considerable debate. Yet, scholarly examination of the Chinese public's attitudes toward this policy, which is crucial for guiding China's strategic directions, remains limited. To address this gap, this paper collects 256,233 Sina Weibo posts from 2021 to 2023 and utilizes text mining methods such as temporal and trend analysis, keyword analysis, topic analysis, and sentiment analysis to investigate the attitudes and emotions of the Chinese people towards common prosperity. The posts holding negative sentiments are also analyzed, so as to uncover the underlying reasons for the dissatisfaction among Chinese citizens regarding common prosperity. Our analysis reveals that China's strategy for promoting common prosperity is primarily focused on economic development rather than wealth redistribution. Emphasis is placed on enhancing education, achieving regional balance, implementing market-oriented reforms, and improving livelihoods. Notably, there is increasing public dissatisfaction, particularly with issues such as irregularities in financial and real estate markets, growing wealth inequality, exploitation by capital, generation of illicit income, and regional development imbalances. These challenges necessitate urgent and effective policy interventions.
引用
收藏
页数:28
相关论文
共 50 条
  • [1] Public attitudes and sentiments toward ChatGPT in China: A text mining analysis based on social media
    Lian, Ying
    Tang, Huiting
    Xiang, Mengting
    Dong, Xuefan
    [J]. TECHNOLOGY IN SOCIETY, 2024, 76
  • [2] Public attitudes and sentiments towards new energy vehicles in China: A text mining approach
    Wu, Zezhou
    He, Qiufeng
    Li, Jiarun
    Bi, Guoqiang
    Antwi-Afari, Maxwell Fordjour
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2023, 178
  • [3] Trends on Organ Transplantation and Donation Based on Public Sentiments Expressed in Social Media Comments in Korea: Text Mining Analysis.
    Ko, H.
    Ahn, H.
    [J]. AMERICAN JOURNAL OF TRANSPLANTATION, 2022, 22 : 919 - 919
  • [4] Mining the impact of social media information on public green consumption attitudes: a framework based on ELM and text data mining
    Fan, Jun
    Peng, Lijuan
    Chen, Tinggui
    Cong, Guodong
    [J]. HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS, 2024, 11 (01):
  • [5] Mining the impact of social media information on public green consumption attitudes: a framework based on ELM and text data mining
    Jun Fan
    Lijuan Peng
    Tinggui Chen
    Guodong Cong
    [J]. Humanities and Social Sciences Communications, 11
  • [6] Public attitudes on open source communities in China: A text mining analysis
    Hou, Shengjie
    Zhang, Xiang
    Yi, Biyi
    Tang, Yi
    [J]. TECHNOLOGY IN SOCIETY, 2022, 71
  • [7] Green housing on social media in China: A text mining analysis
    Shen, Chen
    Li, Ping
    [J]. BUILDING AND ENVIRONMENT, 2023, 237
  • [8] Attitudes of the public and medical professionals toward nurse prescribing: A text-mining study based on social medias
    Zhou, Qi
    Xu, Yiqing
    Yang, Lili
    Menhas, Rashid
    [J]. INTERNATIONAL JOURNAL OF NURSING SCIENCES, 2024, 11 (01) : 99 - 105
  • [9] Social Media Text Analysis on Public's Sentiments of Covid-19 Booster Vaccines
    Kristian, Yohan
    Yesenia, Adira Valdi
    Safina, Safina
    Pravitasari, Anindya Apriliyanti
    Sari, Eka Novita
    Herawan, Tutut
    [J]. COMPUTATIONAL SCIENCE AND ITS APPLICATIONS-ICCSA 2023 WORKSHOPS, PT I, 2023, 14104 : 209 - 224
  • [10] Detecting changes in attitudes toward depression on Chinese social media: A text analysis
    Yu, Lixia
    Jiang, Wanyue
    Ren, Zhihong
    Xu, Sheng
    Zhang, Lin
    Hu, Xiangen
    [J]. JOURNAL OF AFFECTIVE DISORDERS, 2021, 280 : 354 - 363