The potential for collaboration between AI and archival science in processing data from the French great national debate

IF 0.8 Q3 INFORMATION SCIENCE & LIBRARY SCIENCE
M. Chabin
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引用次数: 10

Abstract

Purpose The purpose of this paper is to show how archival expertise and diplomatic analysis can enrich the documentary corpuses analyzed by artificial intelligence tools. Here, the demonstration is based on a freely accessible material: the data from the great national debate launched in early 2019 by the French President Macron in response to the large-scale social movement known as the “yellow vests”. Design/methodology/approach Step 1 consisted of understanding the methods and conclusions of the providers responsible for processing the data of the great debate (1.5 million contributors). Step 2 was to analyze the formal elements of a random set of online contributions. Then, to compare the results. Findings This research shows that the processing of the data is based almost exclusively on texts, to the detriment of data on the source, date and arrangement of contributions, which could nevertheless be exploited as metadata. Research limitations/implications The mass of data and the lack of online accessibility of part of the corpus did not make it possible to complete the experiment. Practical implications This research lays the foundation for other projects for collaboration between archival science and artificial intelligence tools. Social implications There is a social challenge involving researchers in information sciences in public debate and governmental consultations. There is also an issue for a records manager to become more involved in the production of public records by promoting their specific skills in information management. Originality/value The originality of this paper is to show how archival science can help to improve the quality of the documentary corpuses used by artificial intelligence tools, and therefore, to improve the performance of these tools.
人工智能和档案科学在处理法国全国大辩论数据方面的合作潜力
目的本文旨在展示档案专业知识和外交分析如何丰富人工智能工具分析的纪录片公司。在这里演示基于一种可自由获取的材料:2019年初法国总统马克龙为应对被称为“黄背心”的大规模社会运动而发起的全国性大辩论的数据。设计/方法论/方法第一步包括了解负责处理大辩论数据的提供方的方法和结论(150万贡献者)。第二步是分析一组随机在线投稿的形式元素。然后,对结果进行比较。研究结果这项研究表明,数据的处理几乎完全基于文本,这损害了关于投稿来源、日期和安排的数据,尽管如此,这些数据仍可以被用作元数据。研究局限性/含义大量的数据和部分语料库缺乏在线可访问性,无法完成实验。实践意义本研究为档案科学与人工智能工具之间的其他合作项目奠定了基础。社会含义信息科学研究人员参与公共辩论和政府咨询是一项社会挑战。还有一个问题是,档案管理员要通过提高信息管理方面的特定技能,更多地参与公共档案的制作。独创性/价值本文的独创性在于展示档案科学如何有助于提高人工智能工具使用的纪录片的质量,从而提高这些工具的性能。
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来源期刊
Records Management Journal
Records Management Journal INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
3.50
自引率
7.10%
发文量
11
期刊介绍: ■Electronic records management ■Effect of government policies on record management ■Strategic developments in both the public and private sectors ■Systems design and implementation ■Models for records management ■Best practice, standards and guidelines ■Risk management and business continuity ■Performance measurement ■Continuing professional development ■Consortia and co-operation ■Marketing ■Preservation ■Legal and ethical issues
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