A Chinese ancient book digital humanities research platform to support digital humanities research

Abstract

Purpose With the rapid development of digital humanities, some digital humanities platforms have been successfully developed to support digital humanities research for humanists. However, most of them have still not provided a friendly digital reading environment and practicable social network analysis tool to support humanists on interpreting texts and exploring characters’ social network relationships. Moreover, the advancement of digitization technologies for the retrieval and use of Chinese ancient books is arising an unprecedented challenge and opportunity. For these reasons, this paper aims to present a Chinese ancient books digital humanities research platform (CABDHRP) to support historical China studies. In addition to providing digital archives, digital reading, basic search and advanced search functions for Chinese ancient books, this platform still provides two novel functions that can more effectively support digital humanities research, including an automatic text annotation system (ATAS) for interpreting texts and a character social network relationship map tool (CSNRMT) for exploring characters’ social network relationships. Design/methodology/approach This study adopted DSpace, an open-source institutional repository system, to serve as a digital archives system for archiving scanned images, metadata, and full texts to develop the CABDHRP for supporting digital humanities (DH) research. Moreover, the ATAS developed in the CABDHRP used the Node.js framework to implement the system’s front- and back-end services, as well as application programming interfaces (APIs) provided by different databases, such as China Biographical Database (CBDB) and TGAZ, used to retrieve the useful linked data (LD) sources for interpreting ancient texts. Also, Neo4j which is an open-source graph database management system was used to implement the CSNRMT of the CABDHRP. Finally, JavaScript and jQuery were applied to develop a monitoring program embedded in the CABDHRP to record the use processes from humanists based on xAPI (experience API). To understand the research participants’ perception when interpreting the historical texts and characters’ social network relationships with the support of ATAS and CSNRMT, semi-structured interviews with 21 research participants were conducted. Findings An ATAS embedded in the reading interface of CABDHRP can collect resources from different databases through LD for automatically annotating ancient texts to support digital humanities research. It allows the humanists to refer to resources from diverse databases when interpreting ancient texts, as well as provides a friendly text annotation reader for humanists to interpret ancient text through reading. Additionally, the CSNRMT provided by the CABDHRP can semi-automatically identify characters’ names based on Chinese word segmentation technology and humanists’ support to confirm and analyze characters’ social network relationships from Chinese ancient books based on visualizing characters’ social networks as a knowledge graph. The CABDHRP not only can stimulate humanists to explore new viewpoints in a humanistic research, but also can promote the public to emerge the learning interest and awareness of Chinese ancient books. Originality/value This study proposed a novel CABDHRP that provides the advanced features, including the automatic word segmentation of Chinese text, automatic Chinese text annotation, semi-automatic character social network analysis and user behavior analysis, that are different from other existed digital humanities platforms. Currently, there is no this kind of digital humanities platform developed for humanists to support digital humanities research.

Development and application of a digital humanities research platform for biographies of Malaysian personalities

“…Table 1 shows the function comparison of different digital humanities platforms. Among the comparison, the CABDHRP co-developed by the National Central Library and National Chengchi University of Taiwan provides visualization analysis of word frequency statistics, automatic text annotation, semi-automatically SNA, and so forth to support digital humanities research (Chen and Chang, 2019). The CULTURA system consists of multiple distinct services including personalized search tools, faceted search tools, annotators, social network visualization tools, recommenders and so on (Steiner et al , 2014).…”

“…The close reading supports humanities scholars to read the scanned image with the corresponding full-text in a convenient way, whereas distant reading tools offer automatic text annotation, spatio-temporal geographic information analysis and a novel characters’ relationships analysis with the link to the close reading of the original text to assist humanists in more efficiently exploring the historical and cultural development of Chinese in Malaysia. Compared with the character social network relationship map tool (CSNRMT) offered by the Chinese ancient books digital humanities research platform (CABDHRP), which semi-automatically generate the characters’ social network relationships graph without a character relationship recognition mechanism from texts based on Chinese named entity recognition (CNER) technology, to assist humanists in interpreting characters’ relationships hidden in texts (Chen and Chang, 2019), the characters’ relationships analysis tool of the DHRP-BMP developed in this study can automatically generate the characters’ social network relationships graph hidden in texts based on CNER and character relationship recognition technologies to assist humanists in more efficiently and accurately exploring the characters’ social network relationships. Importantly, this study overcomes the technical problems of automatically generating characters’ social network relationships graph hidden in texts and broadens the horizon of the development of digital humanities research platform.…”

Text analysis using deep neural networks in digital humanities and information science

“…For example, the IMDb dataset contains a short description of a movie, and its review score allows to research sentiment analysis (Maas et al, 2011); question answering system can be developed using Stanford Question Answering Dataset (Rajpurkar et al, 2018); and SPAM filtering can be developed using a dedicated dataset (Almeida et al, 2013). Unfortunately, the DH community has not (as yet) produced large annotated open datasets for researches (although there are few in niche areas like [Chen & Chang, 2019;Rubinstein, 2019]). The lack of annotated data is a challenge for both classical machine learning and deep learning supervised algorithms (Elmalech & Dishi, 2021).…”

TwinNet: A Symmetrically Structured Convolutional Architecture for Identifying Tibetan Characters

“…Since the beginning of the new century, scholars have made great contributions to the compilation of historical materials of Chinese ethnic minorities. New technical methods have also been gradually applied in the related fields, such as digitization of ancient books [1], intelligent text recognition [2], VR [3], deep learning [4], etc. This undoubtedly played a positive role in the prosperity and inheritance of Chinese minority culture.…”