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International journal of digital humanities最新文献

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Reproducibility and explainability in digital humanities 数字人文的可复制性和可解释性
Pub Date : 2023-12-04 DOI: 10.1007/s42803-023-00078-7
Thorsten Ries, Karina van Dalen-Oskam, Fabian Offert
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引用次数: 0
Minimal research compendiums: an approach to advance statistical validity and reproducibility in digital humanities research 最小的研究纲要:一种在数字人文研究中推进统计有效性和可重复性的方法
Pub Date : 2023-11-06 DOI: 10.1007/s42803-023-00074-x
Nabeel Siddiqui
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引用次数: 1
A documentation checklist for (Linked) humanities data (链接的)人文数据的文档清单
Pub Date : 2023-11-06 DOI: 10.1007/s42803-023-00072-z
Sarah Middle
Abstract Documentation, including information, instructions, and use cases, is key to reproducibility in Digital Humanities research and usability of resulting tools and resources. However, despite multiple studies that support this assertion, clear and comprehensive documentation is often lacking due to fundamental incompatibilities with existing funding models and the resulting prioritisation of project tasks. Through a user study of researchers involved in using and producing Linked Ancient World Data, supplemented by existing literature, I identified components for inclusion in documentation to facilitate use of these tools and resources, as well as the reproducibility of methods used in their production. At the same time, it became clear that producers would benefit from a solution to simplify the process of documentation creation. As a result, I assembled a documentation checklist whose scope for application reaches beyond Linked Ancient World Data to other Humanities disciplines and digital methods. This paper starts by discussing previous work, before providing an overview of my survey and interview methods. I then present my findings and discuss their implications for future research and development, including an introduction to the checklist and its implementation. To conclude, I draw together threads from the preceding sections and suggest wider structural changes to further facilitate and promote transparency and reproducibility in Digital Humanities.
摘要文档,包括信息、说明和用例,是数字人文研究的可重复性和结果工具和资源的可用性的关键。然而,尽管有多项研究支持这一说法,但由于与现有资助模式的根本不兼容以及由此产生的项目任务优先级,往往缺乏清晰而全面的文件。通过对参与使用和生产关联古代世界数据的研究人员进行用户研究,并辅以现有文献,我确定了在文档中包含的组件,以促进这些工具和资源的使用,以及在其生产中使用的方法的可重复性。同时,很明显制作人将从简化文档创建过程的解决方案中受益。因此,我汇编了一个文档清单,其应用范围超出了链接古代世界数据到其他人文学科和数字方法。本文首先讨论了以前的工作,然后概述了我的调查和访谈方法。然后,我展示了我的发现,并讨论了它们对未来研究和发展的影响,包括对清单及其实施的介绍。最后,我从前面的章节中总结出一些线索,并建议更广泛的结构变化,以进一步促进和促进数字人文学科的透明度和可重复性。
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引用次数: 1
Repetitive research: a conceptual space and terminology of replication, reproduction, revision, reanalysis, reinvestigation and reuse in digital humanities 重复研究:数字人文学科中复制、再生产、修正、再分析、再调查和再利用的概念空间和术语
Pub Date : 2023-11-06 DOI: 10.1007/s42803-023-00073-y
Christof Schöch
Abstract This article is motivated by the ‘reproducibility crisis’ that is being discussed intensely in fields such as Psychology or Biology but is also becoming increasingly relevant to Artificial Intelligence, Natural Language Processing and Digital Humanities, not least in the context of Open Science. Using the phrase ‘repetitive research’ as an umbrella term for a range of practices from replication to follow-up research, and with the objective to provide clarity and help establish best practices in this area, this article focuses on two issues: First, the conceptual space of repetitive research is described across five key dimensions, namely those of the research question or hypothesis, the dataset, the method of analysis, the team, and the results or conclusions. Second, building on this new description of the conceptual space and on earlier terminological work, a specific set of terms for recurring scenarios of repetitive research is proposed. For each scenario, its position in the conceptual space is defined, its typical purpose and added value in the research process are discussed, the requirements for enabling it are described, and illustrative examples from the domain of Computational Literary Studies are provided. The key contribution of this article, therefore, is a proposal for a transparent terminology underpinned by a systematic model of the conceptual space of repetitive research.
这篇文章的动机是“可重复性危机”,这在心理学或生物学等领域正在被激烈讨论,但也越来越多地与人工智能、自然语言处理和数字人文科学相关,尤其是在开放科学的背景下。本文将“重复研究”一词作为从复制到后续研究的一系列实践的总称,目的是提供清晰度并帮助建立该领域的最佳实践,本文重点关注两个问题:首先,重复研究的概念空间跨越五个关键维度,即研究问题或假设、数据集、分析方法、团队和结果或结论。其次,在概念空间的新描述和早期术语工作的基础上,提出了一套用于重复研究的重复场景的特定术语。对于每个场景,定义了其在概念空间中的位置,讨论了其在研究过程中的典型目的和附加价值,描述了实现它的要求,并提供了来自计算文学研究领域的说述性示例。因此,本文的关键贡献是提出了一个透明的术语,该术语以重复研究的概念空间的系统模型为基础。
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引用次数: 1
On reading and interpreting black box deep neural networks 解读黑盒深度神经网络
Pub Date : 2023-11-01 DOI: 10.1007/s42803-023-00075-w
James E. Dobson
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引用次数: 0
eXplainable AI with GPT4 for story analysis and generation: A novel framework for diachronic sentiment analysis 使用GPT4进行故事分析和生成的可解释AI:历时情感分析的新框架
Pub Date : 2023-10-11 DOI: 10.1007/s42803-023-00069-8
Jon Chun, Katherine Elkins
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引用次数: 1
Reproducibility of Indian DH Projects: A case study 印度卫生保健项目的可重复性:一个案例研究
Pub Date : 2023-10-05 DOI: 10.1007/s42803-023-00071-0
Jyothi Justin, Nirmala Menon
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引用次数: 1
Explainability and transparency in the realm of digital humanities: toward a historian XAI 数字人文领域的可解释性和透明性:走向一个历史学家
Pub Date : 2023-10-02 DOI: 10.1007/s42803-023-00070-1
Hassan El-Hajj, Oliver Eberle, Anika Merklein, Anna Siebold, Noga Shlomi, Jochen Büttner, Julius Martinetz, Klaus-Robert Müller, Grégoire Montavon, Matteo Valleriani
Abstract The recent advancements in the field of Artificial Intelligence (AI) translated to an increased adoption of AI technology in the humanities, which is often challenged by the limited amount of annotated data, as well as its heterogeneity. Despite the scarcity of data it has become common practice to design increasingly complex AI models, usually at the expense of human readability, explainability, and trust. This in turn has led to an increased need for tools to help humanities scholars better explain and validate their models as well as their hypotheses. In this paper, we discuss the importance of employing Explainable AI (XAI) methods within the humanities to gain insights into historical processes as well as ensure model reproducibility and a trustworthy scientific result. To drive our point, we present several representative case studies from the Sphaera project where we analyze a large, well-curated corpus of early modern textbooks using an AI model, and rely on the XAI explanatory outputs to generate historical insights concerning their visual content. More specifically, we show that XAI can be used as a partner when investigating debated subjects in the history of science, such as what strategies were used in the early modern period to showcase mathematical instruments and machines.
人工智能(AI)领域的最新进展转化为人工智能技术在人文学科中的应用越来越多,这往往受到注释数据数量有限及其异质性的挑战。尽管数据稀缺,但设计越来越复杂的人工智能模型已经成为一种普遍做法,通常以牺牲人类的可读性、可解释性和信任为代价。这反过来又导致对工具的需求增加,以帮助人文学者更好地解释和验证他们的模型以及他们的假设。在本文中,我们讨论了在人文学科中使用可解释人工智能(XAI)方法的重要性,以深入了解历史进程,并确保模型的可重复性和值得信赖的科学结果。为了推动我们的观点,我们提出了来自Sphaera项目的几个代表性案例研究,我们使用人工智能模型分析了一个大型的、精心策划的早期现代教科书语料库,并依靠XAI解释性输出来生成有关其视觉内容的历史见解。更具体地说,我们表明,在调查科学史上有争议的主题时,可以使用XAI作为合作伙伴,例如在现代早期使用什么策略来展示数学工具和机器。
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引用次数: 2
Measuring digital humanities learning requirements in Spanish & English-speaking practitioner communities 测量西班牙语和英语从业者社区的数字人文学习要求
Pub Date : 2023-09-04 DOI: 10.1007/s42803-023-00066-x
Adam Crymble, Charlotte M. H. Im
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引用次数: 0
Reproducibility and non-traditional authorship attribution: Invitatio ad Arma 再现性和非传统作者归属:邀请与武装
Pub Date : 2023-08-31 DOI: 10.1007/s42803-023-00067-w
J. Rudman
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引用次数: 1
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International journal of digital humanities
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