The anatomy of a search and mining system for digital humanities

Chang

2021

LHT

PurposeDigital humanities aim to use a digital-based revolutionary new way to carry out enhanced forms of humanities research more effectively and efficiently. This study develops a character social network relationship map tool (CSNRMT) that can semi-automatically assist digital humanists through human-computer interaction to more efficiently and accurately explore the character social network relationships from Chinese ancient texts for useful research findings.Design/methodology/approachWith a counterbalanced design, semi-structured in-depth interview, and lag sequential analysis, a total of 21 research subjects participated in an experiment to examine the system effectiveness and technology acceptance of adopting the ancient book digital humanities research platform with and without the CSNRMT to interpret the characters and character social network relationships.FindingsThe experimental results reveal that the experimental group with the CSNRMT support appears higher system effectiveness on the interpretation of characters and character social network relationships than the control group without the CSNRMT, but does not achieve a statistically significant difference. Encouragingly, the experimental group with the CSNRMT support presents remarkably higher technology acceptance than the control group without the CSNRMT. Furthermore, use behaviors analyzed by lag sequential analysis reveal that the CSNRMT could assist digital humanists in the interpretation of character social network relationships. The results of the interview present positive opinions on the integration of system interface, smoothness of operation, and external search function.Research limitations/implicationsCurrently, the system effectiveness of exploring the character social network relationships from texts for useful research findings by using the CSNRMT developed in this study will be significantly affected by the accuracy of recognizing character names and character social network relationships from Chinese ancient texts. The developed CSNRMT will be more practical when the offered information about character names and character social network relationships is more accurate and broad.Practical implicationsThis study develops an ancient book digital humanities research platform with an emerging CSNRMT that provides an easy-to-use real-time interaction interface to semi-automatically support digital humanists to perform digital humanities research with the need of exploring character social network relationships.Originality/valueAt present, a real-time social network analysis tool to provide a friendly interaction interface and effectively assist digital humanists in the digital humanities research with character social networks analysis is still lacked. This study thus presents the CSNRMT that can semi-automatically identify character names from Chinese ancient texts and provide an easy-to-use real-time interaction interface for supporting digital humanities research so that digital humanists could more efficiently and accurately establish character social network relationships from the analyzed texts to explore complicated character social networks relationship and find out useful research findings.

Section: Literature Reviewmentioning

confidence: 99%

A character social network relationship map tool to facilitate digital humanities research

Chang

2021

LHT

“…Also, Brooke et al (2015) introduced a software tool, GutenTag, which is aimed at giving literary researchers direct access to NLP techniques for the analysis of texts in the Project Gutenberg corpus. Harris et al (2014) presented the anatomy of Samtla, which is an online integrated research environment designed in collaboration with historians and linguists, to facilitate the study of digitized texts written in any language. Samtla is fundamentally different from standard text search/mining systems which rely on the bag-of-words representation of text.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The result of their study shows acceptable performance, which is on par with previously reported studies. Although there have been a lot of digital tools to be successfully developed to support DH research, Harris et al (2014) argued that there is still a huge gap between what humanists actually want and what digital tools can do in terms of functionality and usability.…”

Section: Literature Reviewmentioning

confidence: 99%

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

Chang

2019

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.

J. Comput. Cult. Herit.

“…Here the notion of "finding" is divided into search (i.e., locating exact and approximate parallel passages with respect to a given text segment, across multiple documents), and the other refers to discovery (i.e., identifying potentially related text segments). The domain-independent and language-independent digital infrastructure introduced in this paper is at the core of the Samtla (Search And Mining Tools for Language Archives) system 1 [21,22] which has been designed in collaboration with historians, and linguists. Samtla is a web application , based on the a Model-View-Controller (MVC) design pattern [33], and developed in Python 2 using the Django 3 web framework.…”

Section: Introductionmentioning

confidence: 99%

Finding Parallel Passages in Cultural Heritage Archives

Harris

Levene

Zhang

et al. 2018

Self Cite

It is of great interest to researchers and scholars in many disciplines (particularly those working on cultural heritage projects) to study parallel passages (i.e., identical or similar pieces of text describing the same thing) in digital text archives. Although there exist a few software tools for this purpose, they are restricted to a specific domain (e.g., the Bible) or a specific language (e.g., Hebrew). In this paper, we present in detail how we build a digital infrastructure that can facilitate the search and discovery of parallel passages for any domain in any language. It is at the core of our Samtla (Search And Mining Tools with Linguistic Analysis) system designed in collaboration with historians and linguists. The system has already been used to support research on five large text corpora that span a number of different domains and languages. The key to such a domain-independent and language-independent digital infrastructure is a novel combination of a character-based n-gram language model, space-optimised suffix tree, generalised edit distance. A comprehensive evaluation through crowd-sourcing shows that the effectiveness of our system's search functionality is on par with the human-level performance.