Knot

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: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Chang

2021

LHT

The Network Turn

Ahnert

Coleman

et al. 2020

2013, as the leak by Edward Snowden brought to light, the National Security Agency was engaged in massive-scale network analysis using data from nine internet providers.The study and critique of networks has predominantly taken place within the domains of computer science and related scientific fields, the military, and the tech sector due to the scale of digital data being analysed and the nature of the investigations prompting their study. This book not only argues that arts and humanities scholars can use the same kind of visual and quantitative analysis of networks to shed light on the study of culture; it also contends that the critical skills native to humanistic inquiry are vital to the theorisation and critique of our networked world. Network analysis, as we define it in this book, is a set of practices and discourses that sit at the interface of the natural sciences, humanities, social sciences, computer science, and design. We contend that networks are a category of study that cuts across traditional academic boundaries and that has the potential to unite diverse disciplines through a shared understanding of complexity in our worldwhether that complexity pertains to the nature of the interactions of proteins in gene-regulatory networks or to the network of textual variants that can reveal the lineage of a poem. Moreover, this shared framework provides a compelling case for collaboration across those boundaries, for bringing together computational tools for quantitative network analysis, together with theories, discourses, and applied techniques from the social sciences, the humanities, visual design, and art practice.The cases of Lombardi and Barabási provide an instructive way of grasping that shared framework because, superficially, their work has very little in common. Barabási and Albert explicitly cite the computerisation of data acquisition as essential to their research. By contrast, Lombardi's research process was analogue. He gathered his data on three-by-five notecards. There is no evidence that Lombardi read Barabási and Albert's groundbreaking work in statistics and physics; rather, his inspiration was panorama and history painting. He used the term 'narrative structures' to describe his handdrawn webs of connection. Produced through an iterative process of refinement, the work is human in scale, legible visually in its entirety. Perhaps more importantly, it is his interpretation of a carefully researched but inevitably incomplete record. It does not pretend to objectivity. In stark contrast, Barabási 4Publishing and Book Culture

2014 18th International Conference on Information Visualisation

HistoGraph -- A Visualization Tool for Collaborative Analysis of Networks from Historical Social Multimedia Collections

Novak

Micheel

Melenhorst³

et al. 2014

Abstract-This paper describes the design and development of histoGraph, an interactive tool for explorative visualization and collaborative investigation of historical social networks from multimedia collections. Developed in an interdisciplinary collaboration of computer scientists, historians, HCI researchers and interface designers, the tool aims at supporting historians in the discovery and historical analysis of relationships between people, places and events. A special focus is on the identification and interactive visualization of social relations from historical photo collections through a combination of automatic analysis and expert-based crowdsourcing. The tool design bridges the gap between established network analysis and visualization techniques and traditional hermeneutic research methods in historical research. It integrates visual exploration with hybrid social graph construction, hypothesis formulation and the consultation of digitized primary sources. A formative evaluation of the current prototype, developed as a domainspecific application for historians in the field of European integration points to opportunities and critical factors in applying this approach to support and further current research practices in digital humanities.