Related Experiment Video
Updated: Jul 5, 2025

Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling
Published on: January 17, 2025
Analysis of public opinion on employment issues using a combined approach: a case study in China
Chang-Feng Chen1,2, Heng-Yu He3, Yu-Xing Tong3
1College of Computer Science and Engineering, Jishou University, Jishou, 416000, China. changfeng@graduate.utm.my.
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.
More Related Videos
06:34A Component-resolved Diagnostic Approach for a Study on Grass Pollen Allergens in Chinese Southerners with Allergic Rhinitis and/or Asthma
Published on: June 4, 2017
08:24The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
Published on: August 25, 2023
Related Concept Videos
Surveys
Data Collection by Survey
Stereotypes, Prejudice, and Discrimination
Confirmation Biases
Social Proof
Friedman Two-way Analysis of Variance by Ranks