Uncovering Topics of Public Cultural Activities: Evidence from China

In this study, we uncover the topics of Chinese public cultural activities in 2020 with a two-step short textclustering (self-taught neural networks and graph-based clustering) and topic modeling approach. The datasetwe use for this research is collected from 108 websites of libraries and cultural centers, containing over17,000 articles. With the novel framework we propose, we derive 3 clusters and 8 topics from 21 provinciallevel regions in China. By plotting the topic distribution of each cluster, we are able to shows uniquetendencies of local cultural institutes, that is, free lessons and lectures on art and culture, entertainment andservice for socially vulnerable groups, and the preservation of intangible cultural heritage respectively. Thefindings of our study provide decision-making support for cultural institutes, thus promoting public culturalservice from a data-driven perspective.