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

机译:从法国大国家辩论处理数据中AI和档案科学之间的合作潜力

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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.
机译:目的 - 本文的目的是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。在这里,示范基于自由无障碍的材料:由法国总统MECRON于2019年初推出的伟大国家辩论的数据,以应对称为“黄色背心”的大规模社会运动。设计/方法/方法 - 步骤1了解负责处理伟大辩论数据(150万贡献者)的提供者的方法和结论。第2步是分析随机在线贡献的正式要素。然后,比较结果。调查结果 - 本研究表明,数据处理几乎完全基于文本,以损害源,日期和贡献排列的数据,这可能是由元数据被开发。研究限制/影响 - 数据质量和部分组件的在线可访问性并未使其完成实验。实际意义 - 该研究为其他项目奠定了档案科学和​​人工智能工具之间的合作的基础。社会影响 - 涉及公开辩论和政府磋商中的信息科学研究人员存在社会挑战。记录经理还有一个问题,以通过促进其特定技能在信息管理原创/价值中促进其特定技能来制作公共记录 - 本文的原创性是展示档案科学如何有助于提高质量人工智能工具使用的纪录片语料,因此,提高这些工具的性能。

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