Using Digital Humanities Tools to Explore the Implementation of Topic and Sentiment Analysis in Archival Affairs Commentary

Abstract

This paper collected forum discussions related to archives in mainland China and analyzed the topics and sentiment trends presented in archives posts in 2019-2020. This paper used the NLPIR platform to perform text preprocessing such as word segmentation, part-of-speech tagging, and word frequency statistics. Chinese sentiment vocabulary ontology is then introduced to precede the sentiment analysis. The results showed that the topics that people are most concerned about are generally divided into two types. One is the specific figures and events, the other is the social issues represented by “archival work practice” and “archives access”. In terms of sentiment analysis, the archival affairs forum showed obvious negative emotions when discussing specific people and events; and when it came to the practice of archival work, it showed positive expectations for the archival access.

Keywords

• archive posts
• text sentiment analysis
• social media
• archive topics
• mainland china