外国文学研究 ›› 2021, Vol. 43 ›› Issue (6): 1-13.

• 学术访谈 •    下一篇

当下数字人文研究的核心问题与最新进展:泰德·安德伍德访谈录

冯丽蕙, 泰德·安德伍德   

  • 出版日期:2021-12-25 发布日期:2022-01-03
  • 作者简介:冯丽蕙,上海交通大学外国语学院博士生,主要从事世界文学、数字人文和弗兰寇·莫瑞提研究;泰德·安德伍德,伊利诺伊大学厄巴纳–香槟分校信息科学学院和英文系教授,主要从事机器学习、书籍史、数字图书馆、计算社会科学、文本挖掘、文学社会学以及数字人文等领域的研究。
  • 基金资助:
    国家社科基金重大项目“马克思主义与世界文学研究”(14ZDB082); 国家留学基金委项目资助(201906230066)

The Core Issues and Latest Progress of Current Digital Humanities Research: An Interview with Ted Underwood

Feng Lihui, Ted Underwood   

  • Online:2021-12-25 Published:2022-01-03
  • About author:Lihui Feng is a doctoral student at the School of Foreign Languages, Shanghai Jiao Tong University (Shanghai 200240, China). Her research is mainly focused on the studies of world literature, digital humanities and Franco Moretti. Email: evelynfeng@sjtu.edu.cn; Ted Underwood is a professor both at the School of Information Sciences and the Department of English, University of Illinois, Urbana-Champaign. He works on machine learning, book history, digital libraries, computational social science, text mining, sociology of literature, and digital humanities. Email: tunder@illinois.edu
  • Supported by:
    “Marxism and World Literature Studies” (14ZDB082) sponsored by the National Social Science Fund of China and supported by the China Scholarship Council (201906230066)

内容摘要: 泰德·安德伍德是伊利诺伊大学厄巴纳—香槟分校英文系和信息科学学院的教授。近十年来,在应对“数字”与“人文”之间日趋激烈的对话方面,他一直扮演着一个引领者的角色。安德伍德长期致力于文学跨学科研究,著述丰硕,涵盖机器学习、数字图书馆、文本挖掘、数字人文等。他在专著《远距离的视野:数字证据与文学变化》(2019)中探讨了数字方法如何能帮助我们描述并理解时间跨度更长、弧度更大的文学变化。冯丽蕙在华盛顿大学访学期间(2019—2020),就数字人文、机器学习、统计模型等前沿话题对安德伍德进行了专访。安德伍德评述数字分析的意义时指出,数字分析能以一种鸟瞰式视野,揭示更宏阔的文学史图景,从而彻底改变我们对文学史的看法。他不仅特别强调了数据是一种建构这一事实,又结合当下数字人文研究最新进展,详细阐述了定量分析也可以具有批判性的观点。针对数字人文研究的未来发展趋势,他表明,目前我们需要思考和解决的问题就是如何改变现有的数据科学实践,让其为批评服务。

关键词: 数字人文, 统计模型, 机器学习, 数字分析

Abstract: Ted Underwood, a professor both at the Department of English and the School of Information Sciences, University of Illinois, Urbana-Champaign, has always played a leading role in tackling the intensified conversation between the digital and the humanities over the past decade. Writing in large quantities on the issues of machine learning, digital library, text mining, and digital humanities, Underwood has long been committed to the interdisciplinary studies of literature. In his monograph Distant Horizons: Digital Evidence and Literary Change (2019), Underwood makes an exploration of how digital methods can help us describe and comprehend the larger arcs of literary change across longer time spans. During her visit to the University of Washington (2019-2020), Feng Lihui carried out an interview with Underwood on a wide spectrum of cutting-edge topics, including digital humanities, machine learning, and statistical models. When commenting on the significance of digital analysis, Underwood points out that digital analysis, with a bird's-eye view, can bring to light a broader landscape of literary history, thus drastically revolutionizing how we perceive literary history. Not only does he lay particular emphasis on the fact that data is a construction, but also he elaborates on the idea that quantitative analysis can also be critical in light of the latest progress of current digital humanities research. With regard to the future trends of digital humanities research, he declares that the problem that we need to reflect on and wrestle with at present is how to change the existing practice of data science to make it work for critique.

Key words: digital humanities, statistical model, machine learning, digital analysis

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