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Analysis of public opinion on employment issues using a combined approach: a case study in China.
Chen, Chang-Feng; He, Heng-Yu; Tong, Yu-Xing; Chen, Xue-Lin.
Affiliation
  • Chen CF; College of Computer Science and Engineering, Jishou University, Jishou, 416000, China. changfeng@graduate.utm.my.
  • He HY; Faculty of Computing, Universiti Teknologi Malaysia, 80310, Skudai, Johor, Malaysia. changfeng@graduate.utm.my.
  • Tong YX; College of Computer Science and Engineering, Jishou University, Jishou, 416000, China.
  • Chen XL; College of Computer Science and Engineering, Jishou University, Jishou, 416000, China.
Sci Rep ; 14(1): 1944, 2024 01 23.
Article in En | MEDLINE | ID: mdl-38253608
ABSTRACT
To analyze the public opinion related to the employment situation, a combined approach is proposed to study the valuable ideas from social media. Firstly, the popularity of public opinion was analyzed according to the time series from a statistical point of view. Secondly, the feature extraction was carried out on the public opinion information, and the thematic analysis of the employment environment was carried out based on the Latent Dirichlet Allocation model. Thirdly, the Bert model was used to analyze the sentiment classification and trend of the employment-related public opinion data. Finally, the employment public opinion texts in different regions were studied based on the spatial sequence popularity analysis, keyword difference analysis. A case study in China is conducted to verify the effectiveness of proposed combined approach. Results shown that the popularity of employment public opinion reached the highest level in March 2022. Public opinions towards employment situation are negative. There is a specific relationship between the popularity of employment public opinion in different provinces.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Public Opinion / Social Media Aspects: Determinantes_sociais_saude Limits: Humans Country/Region as subject: Asia Language: En Journal: Sci Rep Year: 2024 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Public Opinion / Social Media Aspects: Determinantes_sociais_saude Limits: Humans Country/Region as subject: Asia Language: En Journal: Sci Rep Year: 2024 Document type: Article Affiliation country: China