{"title":"从档案到计算机:米歇尔·福柯与数字人文","authors":"H. Schmidgen, Bernhard J. Dotzler, Benno Stein","doi":"10.22148/001c.55795","DOIUrl":null,"url":null,"abstract":"Michel Foucault famously introduced the method of “discourse analysis” in the humanities, especially in historiography. In his Archaeology of Knowledge, originally published in 1969, in particular, Foucault argues for making the history of knowledge the object of discourse analyses. In the context of the current surge of interest in discourse analysis in the field of computer science, however, there are hardly any references to Foucault, partly because he never defined a methodological process that could be operationalized. Nonetheless we argue for re-reading the Archaeology of Knowledge in the context of computer science and the digital humanities. As a matter of fact, there are considerable affinities between Foucault’s search for the regularities of discourse and current projects dealing with the digitization of texts, their indexing, distributional features, stylometry, etc. We show that these projects were already quite prominent in Foucault’s day, to the point that historian Emmanuel Le Roy Ladurie could assert, in 1968, that “the future historian will be a programmer.” A year later, Foucault’s Archaeology of Knowledge actively responded and constructively took up the challenge – which, given the recent advances in machine learning and computational linguistics, strikes us as a crucial move today.","PeriodicalId":33005,"journal":{"name":"Journal of Cultural Analytics","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"From the Archive to the Computer: Michel Foucault and the Digital Humanities\",\"authors\":\"H. Schmidgen, Bernhard J. Dotzler, Benno Stein\",\"doi\":\"10.22148/001c.55795\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Michel Foucault famously introduced the method of “discourse analysis” in the humanities, especially in historiography. In his Archaeology of Knowledge, originally published in 1969, in particular, Foucault argues for making the history of knowledge the object of discourse analyses. In the context of the current surge of interest in discourse analysis in the field of computer science, however, there are hardly any references to Foucault, partly because he never defined a methodological process that could be operationalized. Nonetheless we argue for re-reading the Archaeology of Knowledge in the context of computer science and the digital humanities. As a matter of fact, there are considerable affinities between Foucault’s search for the regularities of discourse and current projects dealing with the digitization of texts, their indexing, distributional features, stylometry, etc. We show that these projects were already quite prominent in Foucault’s day, to the point that historian Emmanuel Le Roy Ladurie could assert, in 1968, that “the future historian will be a programmer.” A year later, Foucault’s Archaeology of Knowledge actively responded and constructively took up the challenge – which, given the recent advances in machine learning and computational linguistics, strikes us as a crucial move today.\",\"PeriodicalId\":33005,\"journal\":{\"name\":\"Journal of Cultural Analytics\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cultural Analytics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22148/001c.55795\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Arts and Humanities\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cultural Analytics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22148/001c.55795","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Arts and Humanities","Score":null,"Total":0}
引用次数: 1
摘要
米歇尔·福柯(Michel Foucault)在人文科学,尤其是史学中引入了著名的“话语分析”方法。尤其是在1969年出版的《知识考古》一书中,福柯主张将知识史作为话语分析的对象。然而,在当前计算机科学领域对话语分析的兴趣激增的背景下,几乎没有提到福柯,部分原因是他从未定义过一个可以操作的方法论过程。尽管如此,我们还是主张在计算机科学和数字人文学科的背景下重读《知识考古学》。事实上,福柯对话语规律的探索与当前处理文本数字化、文本索引、分布特征、风格学等的项目之间存在着相当大的相似性。我们表明,这些项目在福柯时代已经相当突出,历史学家Emmanuel Le Roy Ladurie可以在1968年断言,“未来的历史学家将是一名程序员。”一年后,福柯的《知识考古》积极回应并建设性地接受了这一挑战——鉴于机器学习和计算语言学的最新进展,这在今天给我们的印象是一个至关重要的举措。
From the Archive to the Computer: Michel Foucault and the Digital Humanities
Michel Foucault famously introduced the method of “discourse analysis” in the humanities, especially in historiography. In his Archaeology of Knowledge, originally published in 1969, in particular, Foucault argues for making the history of knowledge the object of discourse analyses. In the context of the current surge of interest in discourse analysis in the field of computer science, however, there are hardly any references to Foucault, partly because he never defined a methodological process that could be operationalized. Nonetheless we argue for re-reading the Archaeology of Knowledge in the context of computer science and the digital humanities. As a matter of fact, there are considerable affinities between Foucault’s search for the regularities of discourse and current projects dealing with the digitization of texts, their indexing, distributional features, stylometry, etc. We show that these projects were already quite prominent in Foucault’s day, to the point that historian Emmanuel Le Roy Ladurie could assert, in 1968, that “the future historian will be a programmer.” A year later, Foucault’s Archaeology of Knowledge actively responded and constructively took up the challenge – which, given the recent advances in machine learning and computational linguistics, strikes us as a crucial move today.