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 38 条
[1]   Sentiment analysis of Arabic social media texts: A machine learning approach to deciphering customer perceptions [J].
Alsemaree, Ohud ;
Alam, Atm S. ;
Gill, Sukhpal Singh ;
Uhlig, Steve .
HELIYON, 2024, 10 (09)
[2]   Applications and Enhancement of Document-Based Sentiment Analysis in Deep learning Methods: Systematic Literature Review [J].
Alshuwaier, Faisal ;
Areshey, Ali ;
Poon, Josiah .
INTELLIGENT SYSTEMS WITH APPLICATIONS, 2022, 15
[3]   Sustainable development of the mining sector for achieving common prosperity in Chinese rural areas [J].
Chen, Yiru ;
He, Mu ;
Xu, Yi .
RESOURCES POLICY, 2023, 87
[4]   Research on the evaluation and configuration path of China's rural common Prosperity-NCA and fsQCA based on provincial panel data [J].
Cheng, Liang ;
Yang, Lihua ;
Li, Xing ;
Xu, Sheng ;
Cao, Ying .
HELIYON, 2024, 10 (01)
[5]  
Collier A., 2022, Chinas Technology War: Why Beijing Took Down Its Tech Giants, P11
[6]   Monitoring the Quality and Perception of Service in Colombian Public Service Companies with Twitter and Descriptive Temporal Analysis [J].
Conti, Dante ;
Gomez, Carlos Eduardo ;
Jaramillo, Juan Guillermo ;
Ospina, Victoria Eugenia .
APPLIED SCIENCES-BASEL, 2023, 13 (18)
[7]   Exploiting affinities between topic modeling and the sociological perspective on culture: Application to newspaper coverage of US government arts funding [J].
DiMaggio, Paul ;
Nag, Manish ;
Blei, David .
POETICS, 2013, 41 (06) :570-606
[8]   How does energy poverty eradication promote common prosperity in China? The role of labor productivity [J].
Dong, Kangyin ;
Wei, Shuo ;
Liu, Yang ;
Zhao, Jun .
ENERGY POLICY, 2023, 181
[9]   The Chinese Path to Common Prosperity [J].
Dunford, Michael .
INTERNATIONAL CRITICAL THOUGHT, 2022, 12 (01) :35-54
[10]  
Eis E., What Is "Common Prosperity"and How Will It Change China