使用综合方法对就业问题进行公众论分析:中国的案例研究
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.
Scientific reports
|January 22, 2024
概括
公众对就业的看法在很大程度上是负面的,在2022年3月达到顶峰. 对社交媒体数据的分析揭示了就业讨论和情绪的区域差异.
科学领域:
- 社会科学 社会科学 社会科学
- 计算社会科学 计算社会科学
- 数据科学数据科学数据科学
背景情况:
- 了解公众对就业的看法对于制定政策至关重要.
- 社交媒体平台提供了丰富的实时公众情绪数据来源.
研究的目的:
- 通过综合方法分析公众对就业状况的看法.
- 从社交媒体数据中提取有关就业的有价值的见解.
主要方法:
- 对流行趋势的时间序列分析.
- 潜在的迪里克莱特分配 (LDA) 用于主题分析.
- 用于情绪分类和趋势分析的BERT模型.
- 区域差异的空间分析.
主要成果:
- 关于就业的公众论受欢迎程度在2022年3月达到顶峰.
- 总体而言,公众对就业状况的看法是负面的.
- 在不同省份的就业讨论的受欢迎程度之间存在明显的关系.
结论:
- 综合方法有效地从社交媒体上分析与就业相关的公众意见.
- 社交媒体数据为公众情绪和地区就业问题提供了重要的见解.
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