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The purpose of this paper is to conduct a retrospective bibliometric analysis of documents about digital humanities, an emerging but interdisciplinary movement. It examines the distribution of research outputs and languages, identifies the active journals and institutions, dissects the network of categories and cited references, and interprets the hot research topics.

The source data are derived from the Web of Science (WoS) core collection. To reveal the holistic landscape of this field, VOSviewer and CiteSpace as popular visualization tools are employed to process the bibliographic data including author, category, reference, and keyword. Furthermore, the parameter design of the visualization tools follows the general procedures and methods for bibliometric analysis.

There is an obviously rapid growth in digital humanities research. English is still the leading academic language in this field. The most influential authors all come from or have scientific relationships with Europe and North America, and two leading countries of which are the UK and USA. Digital humanities is the result of a dynamic dialogue between humanistic exploration and digital means. This research field is closely associated with history, literary and cultural heritage, and information and library science.

This analysis relies on the metadata information extracted from the WoS database; however, some valuable literatures in the field of digital humanities may not be retrieved from the database owing to the inherent challenge of topic search. This study is also restricted by the scope of publications, the limitation regarding the source of data is that WoS database may have underrepresented publications in this domain.

The output of this paper could be a valuable reference for researchers and practitioners interesting in the knowledge domain of digital humanities. Moreover, the conclusions of this retrospective analysis can be deemed as the comparable foundation for future study.

This study aims to develop a hierarchical topic analysis tool (HTAT) based on hierarchical Latent Dirichelet allocation (hLDA) to support digital humanities research that is associated with the need of topic exploration on the Digital Humanities Platform for Mr. Lo Chia-Lun’s Writings (DHP-LCLW). HTAT can assist humanities scholars on distant reading with analysis of hierarchical text topics, through classifying time-stamped texts into multiple historical eras, conducting hierarchical topic modeling (HTM) according to the texts from different eras and presenting through visualization. The comparative network diagram is another function provided to assist humanities scholars in comparing the difference in the topics they wish to explore and to track how the concept of a topic changes over time from a particular perspective. In addition, HTAT can also provide humanities scholars with the feature to view source texts, thus having high potential to be applied in promoting the effectiveness of topic exploration due to simultaneously integrating both the topic exploration functions of distant reading and close reading.

This study adopts a counterbalanced experimental design to examine whether there is significant differences in the effectiveness of topic inquiry, the number of relevant topics inquired and the time spent on them when research participants were alternately conducting text exploration using DHP-LCLW with HTAT or DHP-LCLW with Single-layer Topic Analysis Tool (SLTAT). A technology acceptance questionnaire and semi-structured interviews were also conducted to understand the research participants' perception and feelings toward using the two different tools to assist topic inquiry.

The experimental results show that DHP-LCLW with HTAT could better assist the research participants, in comparison with DHP-LCLW with SLTAT, to grasp the topic context of the texts from two particular perspectives assigned by this study within a short period. In addition, the results of the interviews revealed that DHP-LCLW with HTAT, in comparison with SLTAT, was able to provide a topic terms that better met research participnats' expectations and needs, and effectively guided them to the corresponding texts for close reading. In the analysis of technology acceptance and interview data, it can be found that the research participants have a high and positive tendency toward using DHP-LCLW with HTAT to assist topic inquiry.

The Jieba Chinese word segmentation system was used in the Mr. Lo Chia-Lun’s Writings Database in this study, to perform word segmentation on Mr. Lo Chia-Lun’s writing texts for topic modeling based on hLDA. Since Jieba word segmentation system is a lexicon based word segmentation system, it cannot identify new words that have still not been collected in the lexicon well. In this case, the correctness of word segmentation on the target texts will affect the results of hLDA topic modeling, and the effectiveness of HTAT in assisting humanities scholars for topic inquiry.

An HTAT was developed to support digital humanities research in this study. With HTAT, DHP-LCLW provides hmanities scholars with topic clues from different hierarchical perspectives for textual exploration, and with temporal and comparative network diagrams to assist humanities scholars in tracking the evolution of the topics of specific perspectives over time, to gain a more comprehensive understanding of the overall context of the texts.

In recent years, topic analysis technology that can automatically extract key topic information from a large amount of texts has been developed rapidly, but the topics generated from traditional topic analysis models like LDA (Latent Dirichelet allocation) make it difficult for users to understand the differences in the topics of texts with different hierarchical levels. Thus, this study proposes HTAT which uses hLDA to build a hierarchical topic tree with a tree-like structure without the need to define the number of topics in advance, enabling humanities scholars to quickly grasp the concept of textual topics and use different hierarchical perspectives for further textual exploration. At the same time, it also provides a combination function of temporal division and comparative network diagram to assist humanities scholars in exploring topics and their changes in different eras, which helps them discover more useful research clues or findings.

This article aims to explore how the mapping strategies between user requirements expressed by the humanities researchers lead to a better customization of user-driven digital humanities tools and to the creation of innovative functionalities, which can directly affect the way of doing research in a digital context.

It describes the user-driven development of a tool that helps researchers in the quantitative and qualitative analysis of large textbook collections.

This article presents an exemplary user journey map, which shows the different steps of the digital transformation process and how the humanities researchers are involved for (1) producing innovative research solutions, comprehensive and personalized reports, and (2) customizing access to content data used for the analysis of digital documents. The article is based on a case study on a German textbooks collection and content analysis functionalities.

The focus of this article is the reiterative research process, in which humanists (from the human centred point of view) starts from an initial research question, using quantitative and qualitative data and develops both the research question and the answers to it by with the aim to find patterns in the content and structure of educational media. Thus, from the viewpoint of digital transformation the humanist is part of the interaction between digitization and digitalization processes, where he/she uses digital data, metadata, reports and findings created and supported by the digital tools for research analysis.

Ubiquitous digital technologies are driving organisations to embrace non-traditional digitally transformed business models incessantly. Heterogeneous literature contributions have resulted in a spur in the research related to business transformation driven by digital technologies in recent years; consequently, the research under the digital transformation (DT), even though becoming a hotspot, remains very fragmented. The authors endeavour to holistically present the literature's intellectual structure under DT as a concept, its evolving journey and the emerging research streams in the business and management domains using the techniques of bibliometric analysis.

By performing bibliometric analysis on 234 research articles published over the last 20 years in the DT domain, retrieved from Thompson Reuters Web of Science ^TM, this study culls out thorough insights from the citation, co-citation and keyword analysis. Further emerging research streams were evaluated using VOSviewer software.

The study depicts an overall incremental trend of year-on-year publications, authors' performance, publication journals, associated institutions and research driving countries, along with key insights from co-citation network analysis. Furthermore, the study evaluates four research areas – organisational impacts, applied applications and insights, operational processes and social aspects, comprising eighteen research streams that comprehensively cover-up research under the DT domain.

The study contributes to the literature of DT by amalgamating the status of the present research, but more importantly, by deriving the research areas and research streams, which can be further expanded by researchers as future research streams.

For the practitioners, the study aims to act as a ready reckoner repository with practice-oriented literature references to facilitate them building knowledge and taking effective strategic decisions to harness the benefits of DT more proficiently.

This study illustrates the bibliometric structure of the DT literature and presents insights from the growth of the literature year-on-year.

Digital technology and SDGs have gained increasing interest from the research community. This chapter aims to explore the field through a holistic review of 188 publications from 2017 to 2022. For the systematic review of 188 articles, a three-step methodology comprising of PRISMA guidelines was performed, bibliometric analysis and text analysis using VOS-Viewer and Sentiment Analysis using RStudio had been undertaken. Bibliographic coupling revealed the following clusters Digital Space (Over all SDG), Localising SDGs, Financial Systems and Growth (SDG 8), Sustainable Supply Chain (SDG 9), Education (SDG 4), Energy Management (SDG 7), Smart Cities (SDG 11 and 13), Gender, Skills, and Responsibility (SDG 5 and 12), Food Management (SDG 1, 2 and 3), Business Innovation (SDG 8 and 9) and ICT (SDG 9). Next, co-occurrence analysis highlighted the following clusters Circular Economy (SDG 8), Higher Education System (SDG 4), Digital health (SDG 3), Industry 4.0 (SDG 9) and Supply Chain Management (SDG 9). Next, text analysis traced the most relevant areas of work within the theme. Finally, sentiment analysis revealed positive sentiments of the field. The research concluded that only a few SDGs had found major focus while the others don't have any solid ground in the literature. This chapter presents a knowledge structure by mapping the most relevant SDGs in the context of digital technology and sets directions for future research.

With the aid of bibliometric analysis, this study aims to show the state-of-the-art of research on the digital divide and identifies new areas for further investigation.

Performance analysis and science mapping were used in the study to analyse a sample of 3,571 studies that were published between 2018 and 2022. The “Title-Keyword-Abstract” search option was used to collect the anticipated publications data from the Scopus database. The gathered data were analysed using the common bibliometric indices to evaluate the research landscape. The science mapping tactics made use of the VOSviewer and Biblioshiny software.

The performance and science mapping analysis shows that recent research on the digital divide has not been sufficiently exposed and examined. The analysis discovered emerging topics, prolific authors and nations, affiliations, a network of collaboration among authors, countries and institutions, bibliographic coupling and keyword co-occurrence.

This work presents a state-of-the-art that has significant theoretical and practical ramifications for the existing digital divide literature. The methodologies and database used in the current study are more extensive.

This study aims to explore knowledge structure and research trends in the domain of digital humanities (DH) in the recent decade. The study identified prevailing topics and then, analyzed trends of such topics over time in the DH field.

Research bibliographic data in the area of DH were collected from scholarly databases. Multiple text mining techniques were used to identify prevailing research topics and trends, such as keyword co-occurrences, bigram analysis, structural topic models and bi-term topic models.

Term-level analysis revealed that cultural heritage, geographic information, semantic web, linked data and digital media were among the most popular topics in the recent decade. Structural topic models identified that linked open data, text mining, semantic web and ontology, text digitization and social network analysis received increased attention in the DH field.

This study applied existent text mining techniques to understand the research domain in DH. The study collected a large set of bibliographic text, representing the area of DH from multiple academic databases and explored research trends based on structural topic models.

The purpose of this paper is to determine the digital library usage patterns as a means of improving the system, as well as the user experience, to give appropriate recognition to the most popular dissertations’ authors and to measure the interest of non-academic users for dissertations defended at the University of Novi Sad (UNS).

A logging module of the digital library of theses and dissertations of University of Novi Sad (PHD UNS) application has been implemented. The module recorded the messages relating to the search queries and downloads over a three-year period from 2017–2019. These logs are analysed using the Elasticsearch, Logstash and Kibana (ELK) technology stack and the results are shown using graphs and tables.

The analysis determined the perfect time for weekly maintenance of the system, defined a recommendation for improving the system and revealed the most popular dissertations. A significant number of downloads and queries originated from citizens, i.e. users outside the academic community.

The conducted analysis defined recommendations for the system improvement which can be used by PHD UNS research and development (R&D) team and revealed the most popular dissertations which are used for the promotion of its authors through faculties’ websites.

To the best of the authors’ knowledge, this is the first study of ELK based log analysis of a Serbian language documents’ repository. Besides, the value of results for the PHD UNS R&D team and UNS rector team, the study proves that PhD digital library presents an important Open Science communication channel for presenting scientific results to the citizens.

Digital humanities research platform for biographies of Malaysia personalities (DHRP-BMP) was collaboratively developed by the Research Center for Chinese Cultural Subjectivity in Taiwan, the Federation of Heng Ann Association Malaysia, and the Malaysian Chinese Research Center of Universiti Malaya in this study. Using The Biographies of Malaysia Henghua Personalities as the main archival sources, DHRP-BMP adopted the Omeka S, which is a next-generation Web publishing platform for institutions interested in connecting digital cultural heritage collections with other resources online, as the basic development system of the platform, to develop the functions of close reading and distant reading both combined together as the foundation of its digital humanities tools.

The results of the first-stage development are introduced in this study, and a case study of qualitative analysis is provided to describe the research process by a humanist scholar who used DHRP-BMP to discover the character relationships and contexts hidden in The Biographies of Malaysia Henghua Personalities.

Close reading provided by DHRP-BMP was able to support humanities scholars on comprehending full text contents through a user-friendly reading interface while distant reading developed in DHRP-BMP could assist humanities scholars on interpreting texts from a rather macro perspective through text analysis, with the functions such as keyword search, geographic information and social networks analysis for humanities scholars to master on the character relationships and geographic distribution from personality biographies, thus accelerating their text interpretation efficiency and uncovering the hidden context.

At present, a digital humanities research platform with real-time characters’ relationships analysis tool that can automatically generate visualized character relationship graphs based on Chinese named entity recognition (CNER) and character relationship identification technologies to effectively assist humanities scholars in interpreting characters’ relationships for digital humanities research is still lacking so far. This study thus presents the DHRP-BMP that offers the key features that can automatically identify characters’ names and characters’ relationships from personality biographies and provide a user-friendly visualization interface of characters’ relationships for supporting digital humanities research, so that humanities scholars could more efficiently and accurately explore characters’ relationships from the analyzed texts to explore complicated characters’ relationships and find out useful research findings.

This aim of this paper is to examine the existing gender digital inclusion evaluation guidance and proposes future research recommendations for their evaluation. Despite modern progress in towards gender equality and women’s empowerment movements, women’s access to, use of and benefits from digital technologies remain limited owing to economic, social and cultural obstacles. Addressing the existing gender digital divide is critical in the global efforts towards the United Nations’ Sustainable Development Goals (SDGs). In recent years, there has been a global increase of gender digital inclusion programmes for girls and women; these programmes serve as a mechanism to learn about gender-specific digital needs and inform future digital inclusion efforts. Evaluation reports of gender digital inclusion programmes can produce critical insights into girls’ and women’s learning needs and aspirations, including what works and what does not when engaging girls and women in information and communications technologies. While there are many accounts highlighting the importance of why gender digital inclusion programmes are important, there is limited knowledge on how to evaluate their impact.

The thematic analysis suggests three points to consider for the gender digital inclusion programmes evaluation: context-specific understanding of gender digital inclusion programmes; transparency and accountability of the evaluation process and its results; and tensions between evaluation targets and empowerment of evaluation participants.

The thematic analysis suggests three points of future focus for this evaluation process: context-specific understanding of gender digital inclusion programmes; transparency and accountability of the evaluation process and its results; and tensions between evaluation targets and empowerment of evaluation participants.

The authors propose recommendations for gender digital inclusion evaluation practice and areas for future research.