TY - JOUR
T1 - 当下数字人文研究的核心问题与最新进展
T2 - 泰德•安德伍德访谈录
AU - Feng, Lihui
AU - Underwood, Ted
N1 - Funding Information:
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 Projects: “Marxism and World Literature Studies” (14ZDB082) sponsored by the National Social Science Fund of China and supported by the China Scholarship Council (201906230066) Authors: 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
Publisher Copyright:
© Copyright by Foreign Literature Studies. All right reserved.
PY - 2021/12/25
Y1 - 2021/12/25
N2 - 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.
AB - 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.
KW - Digital analysis
KW - Digital humanities
KW - Machine learning
KW - Statistical model
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M3 - Article
AN - SCOPUS:85122319795
SN - 1003-7519
VL - 43
SP - 1
EP - 13
JO - Foreign Literature Studies
JF - Foreign Literature Studies
IS - 6
ER -