Task design and assignment of full-text generation on mass Chinese historical archives in digital humanities

Liang, Jihong; Wang, Hao; Li, Xiaojing

doi:10.1108/ajim-09-2019-0245

Cited by 8 publications

(11 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the advancement of the internet and digital technology, and the rise of digital databases, the way that humanities scholars collect, analyze and apply data has gradually changed, and thus humanities computing was further developed as the emerging field of digital humanities. Among different types of databases, digital humanities databases that are different from canonical retrieval databases and quantitative analysis databases emphasize statistical descriptions of demographic and social behaviors recorded over long periods of time and on a large scale data (Liang et al. , 2020; Gao et al.…”

Section: Literature Reviewmentioning

confidence: 99%

“…the way that humanities scholars collect, analyze and apply data has gradually changed, and thus humanities computing was further developed as the emerging field of digital humanities. Among different types of databases, digital humanities databases that are different from canonical retrieval databases and quantitative analysis databases emphasize statistical descriptions of demographic and social behaviors recorded over long periods of time and on a large scale data (Liang et al, 2020;Gao et al, 2021). In this way, it can not only reveal the historical processes and patterns hidden under the data, but also present the temporal and spatial connections between related documents and assists humanities scholars in discovering new topics and conducting more efficient research (Liang et al, 2020).…”

Section: Digital Humanities Researchmentioning

confidence: 99%

“…Among different types of databases, digital humanities databases that are different from canonical retrieval databases and quantitative analysis databases emphasize statistical descriptions of demographic and social behaviors recorded over long periods of time and on a large scale data (Liang et al, 2020;Gao et al, 2021). In this way, it can not only reveal the historical processes and patterns hidden under the data, but also present the temporal and spatial connections between related documents and assists humanities scholars in discovering new topics and conducting more efficient research (Liang et al, 2020). Since Taiwan's Digital Archives Program was launched in 2002, a lot of digital archives and databases were developed through the funding support of this program, but what the researchers face today is not a lack of data, the key issue is how to process, analyze and apply such a large amount of data to make it meaningful and valuable (Rosenzweig, 2003).…”

Section: Digital Humanities Researchmentioning

confidence: 99%

“…, 2021). In this way, it can not only reveal the historical processes and patterns hidden under the data, but also present the temporal and spatial connections between related documents and assists humanities scholars in discovering new topics and conducting more efficient research (Liang et al. , 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Liang et al. ’s study (2020) explored the task design and assignment of full-text generation on mass Chinese historical archives (CHAs) by crowdsourcing, particularly in paying attention to how to best divide full-text generation tasks into smaller ones assigned to crowdsourced volunteers and to improve the digitization of mass CHAs and the data-oriented processing of the digital humanities. The above mentioned development has promoted the development of digital humanities infrastructures, and more and more digital humanities research platforms are being established and used around the world (Gao et al.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A hierarchical topic analysis tool to facilitate digital humanities research

Chen

Chang

2022

AJIM

View full text Add to dashboard Cite

PurposeThis 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.Design/methodology/approachThis 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.FindingsThe 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.Research limitations/implicationsThe 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.Practical implicationsAn 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.Originality/valueIn 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.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Digital Humanities Researchmentioning

confidence: 99%

Section: Digital Humanities Researchmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A hierarchical topic analysis tool to facilitate digital humanities research

Chen

Chang

2022

AJIM

View full text Add to dashboard Cite

show abstract

Value co‐creation in cultural heritage information practices: Literature review and future agenda: An Annual Review of Information Science and Technology (ARIST) paper

Zhao,

Lian,

Zhang

et al. 2023

Asso for Info Science & Tech

View full text Add to dashboard Cite

Value co‐creation as a research topic has been a critical proposition of interest to a wide range of disciplines. In recent years, the field of cultural heritage has also developed a range of information practices to promote different forms of value co‐creation. While the body of literature has begun to accumulate, we still lack a comprehensive understanding of conceptual foundations and how value co‐creation is implemented in cultural heritage information practices. This paper conducted a hermeneutic literature review to understand and conceptualize the core aspects of value co‐creation in various cultural heritage information works. In particular, this paper provides a research mapping of the genres of co‐creation in cultural heritage information practices, the actors, and the roles played by the stakeholders. Further, this review provides an overview of the dominant value co‐creation models in the cultural heritage field. It distills the drivers of value co‐creation and the core value consequences that arise from a process perspective. Finally, this paper puts forward a thematic, theoretical, and methodological agenda for future work based on these findings. The review contributes to the literature by proposing an integrated conceptual framework that summarizes the core elements of value co‐creation in cultural heritage information practices. The framework also serves as a call for action, providing a general understanding of the conceptual foundation for future research.

show abstract

Ground-truth generation through crowdsourcing with probabilistic indexes

Sánchez,

Vidal,

Bosch

et al. 2024

Neural Comput & Applic

View full text Add to dashboard Cite

Automatic transcription of large series of historical handwritten documents generally aims at allowing to search for textual information in these documents. However, automatic transcripts often lack the level of accuracy needed for reliable text indexing and search purposes. Probabilistic Indexing (PrIx) offers a unique alternative to raw transcripts. Since it needs training data to achieve good search performance, PrIx-based crowdsourcing techniques are introduced in this paper to gather the required data. In the proposed approach, PrIx confidence measures are used to drive a correction process in which users can amend errors and possibly add missing text. In a further step, corrected data are used to retrain the PrIx models. Results on five large series are reported which show consistent improvements after retraining. However, it can be argued whether the overall costs of the crowdsourcing operation pay off for the improvements, or perhaps it would have been more cost-effective to just start with a larger and cleaner amount of professionally produced training transcripts.

show abstract

Task design and assignment of full-text generation on mass Chinese historical archives in digital humanities

Cited by 8 publications

References 6 publications

A hierarchical topic analysis tool to facilitate digital humanities research

A hierarchical topic analysis tool to facilitate digital humanities research

Value co‐creation in cultural heritage information practices: Literature review and future agenda: An Annual Review of Information Science and Technology (ARIST) paper

Ground-truth generation through crowdsourcing with probabilistic indexes

Contact Info

Product

Resources

About