Uncovering Topics of Public Cultural Activities: Evidence from China

• 作者： Zixin, Zeng ( 1 ) ; Bolin, Hua ( 1 ) ;
• 作者单位： 1.Department of Information Management, Peking University , Beijing 100871, China;
• 提交时间：2022-11-28

摘要：In this study, we uncover the topics of Chinese public cultural activities in 2020 with a two-step short text clustering (self-taught neural networks and graph-based clustering) and topic modeling approach. The dataset we use for this research is collected from 108 websites of libraries and cultural centers, containing over 17,000 articles. With the novel framework we propose, we derive 3 clusters and 8 topics from 21 provincial#2; level regions in China. By plotting the topic distribution of each cluster, we are able to shows unique tendencies of local cultural institutes, that is, free lessons and lectures on art and culture, entertainment and service for socially vulnerable groups, and the preservation of intangible cultural heritage respectively. The findings of our study provide decision-making support for cultural institutes, thus promoting public cultural service from a data-driven perspective.

• 期刊： DATA INTELLIGENCE
• 分类： 计算机科学 >> 计算机科学的集成理论
• 引用： ChinaXiv:202211.00419 (或此版本 ChinaXiv:202211.00419V1)
  (DOI: 10.1162/dint_a_00121)
  (CSTR:32003.36.ChinaXiv.202211.00419.V1)
• 推荐引用方式：Zixin, Zeng,Bolin, Hua.(2022).Uncovering Topics of Public Cultural Activities: Evidence from China.DATA INTELLIGENCE.CSTR:32003.36.ChinaXiv.202211.00419.V1 (点此复制)