[CFP] Computational Humanities Research

새로운 디지털인문학 국제 학술지(Computational Humanities Research) 창간호 원고 모집

Computational Humanities Research (CHR) is an open access journal in the computational humanities, publishing transdisciplinary papers that are grounded in humanities research questions and use computational, quantitative methodologies to analyse humanities data in its various forms. CHR publishes research that tackles big questions and solves problems pertaining to the humanities through advanced computational methods, contributing empirically to major theoretical, cultural, and historical inquiry. It seeks papers that spotlight quantitative and computational methods and applications, including the practical use and impact of computational techniques, in humanities research.

[CFP] Expanding the Toolkit: Large Language Models in Humanities Research.

Expanding the Toolkit: Large Language Models in Humanities Research (cambridge.org)

Computational Humanities Research invites submissions for the upcoming themed issue on Expanding the Toolkit: Large Language Models in Humanities Research.

The deadline for submissions is 30 November 2024.

Themed issue description

Large Language Models (LLMs) are revolutionizing the landscape of humanities research, offering unprecedented opportunities to scale up data analytics and automate qualitative tasks. This themed issue aims to explore the impact of LLMs on humanities research, showcasing innovative approaches, methodologies, and case studies that demonstrate the potential of machine-assisted research in various humanities disciplines.

Topics of interest

We invite researchers to submit extended versions of their papers presented at previous CHR conferences, as well as new contributions that address the theme of LLMs in humanities research. Topics of interest include, but are not limited to:

• Systematic frameworks for integrating LLMs into humanities research methodologies.
• Case studies demonstrating the application of LLMs in various humanities disciplines.
• Challenges and opportunities in using LLMs for non-English and historical texts.
• Ethical considerations and best practices for LLM-assisted humanities research.
• Comparative studies of LLM performance against traditional research methods.
• Novel applications of LLMs in qualitative data analysis, text mining, and cultural analytics.
• Integration of LLMs with other computational methods in humanities research.

Submission process

All submissions should be made via the CHR online peer review system. Authors should consult the journal’s Authors instructions prior to submission.

Contacts

If you have questions about this themed issue, please reach out to Folgert Karsdorp – folgert.karsdorp@meertens.knaw.nl

For any questions relating to editorial policy or the submission process, please contact the journal’s Editorial Office at chr@cambridge.org.

[CFP] Missing Data in the Humanities

Missing Data in the Humanities (cambridge.org)

Computational Humanities Research invites submissions for its upcoming themed issue on Missing Data in the Humanities, which will be edited by Mike Kestemont (University of Antwerp, Belgium) and Folgert Karsdorp (Meertens Institute, The Netherlands).

The deadline for submissions is 1 January 2025.

Themed issue description

Humanities scholars have long grappled with the challenge of incomplete historical records and datasets. This issue, known in German scholarship as Überlieferungschance, permeates various disciplines studying the past, where available data often represents only a fraction of the original historical population. Imperfect registration, survival rates, and inherent biases in preservation result in potentially skewed historical narratives, exemplifying a form of ‘survivorship bias’ in our understanding of the past.

The challenge of missing data extends beyond mere gaps in the historical record. Some types of information are inherently less likely to be captured by physical artifacts such as books or paintings, leading to systematic underrepresentation of certain aspects of historical societies. This bias in material preservation compounds the already complex issue of historical data incompleteness.

Recent years have seen a growing interest in quantifying and addressing these gaps in our historical knowledge. Innovative approaches, such as the application of unseen species models from ecology, are offering new ways to estimate the extent of lost or forgotten data. These methods have found surprising applications across diverse domains in the humanities, from medieval literature to early modern book collections, and from studies of historical professions to criminology.

However, it is crucial to recognize that statistical methods alone cannot fully rectify historical biases. They must be used in conjunction with critical historical analysis, interdisciplinary collaboration, and a commitment to amplifying marginalised voices. This themed issue aims to explore not only the multifaceted challenge of missing data in the humanities and the novel computational methods being developed to address it, but also how these quantitative approaches can be integrated with qualitative methods to provide a more comprehensive and equitable view of historical societies.

Topics of interest

Submissions may address, but are not limited to, the following topics:

1. Theoretical approaches to conceptualising and quantifying missing data in humanities datasets
2. Adaptations of population estimation models (e.g., unseen species models) to humanities contexts
3. Case studies demonstrating innovative methods for estimating historical population sizes
4. Critical reflections on the implications of missing data for historical interpretation
5. Computational approaches to identifying and mitigating survivorship bias in cultural heritage studies
6. Ethical considerations in reconstructing or estimating missing historical information
7. The impact of digital humanities techniques on our understanding of historical data gaps
8. Methodological reflections on the limitations and potential of quantitative approaches to missing data
9. Analyses of biases in material preservation and their impact on historical understanding.

We welcome submissions from scholars across the humanities, including but not limited to history, literature, archaeology, art history, and cultural studies, as well as from computer scientists, mathematicians, statisticians or any other relevant field working on humanities-related projects.

Submission process

All submissions should be made via the CHR online peer review system. Authors should consult the journal’s Authors instructions prior to submission.

Contacts

If you have questions about this themed issue, please reach out to the Guest Editors:

• Folgert Karsdorp, Meertens Institute, The Netherlands – folgert.karsdorp@meertens.knaw.nl
• Mike Kestemont, University of Antwerp, Belgium – mike.kestemont@uantwerp.be

For any questions relating to editorial policy or the submission process, please contact the journal’s Editorial Office at chr@cambridge.org.