杭州电子科技大学图书馆书目检索系统

Online Public Access Catalogue

题名/责任者:

Humanities data analysis : case studies with Python / Folgert Karsdorp, Mike Kestemont & Allen Riddell.

出版发行项:

Princeton ; Oxford : Princeton University Press, 2021.

ISBN:

9780691172361:

ISBN:

0691172366

载体形态项:

xi, 337 pages : illustrations (some color), maps (some color) ; 27 cm

个人责任者:

Karsdorp, Folgert, author.

附加个人名称:

Kestemont, Mike, 1985- author.

附加个人名称:

Riddell, Allen, author.

论题主题:

Humanities-Research-Methodology.

论题主题:

Social sciences-Research-Methodology.

论题主题:

Quantitative research-Data processing.

论题主题:

Python (Computer program language)

中图法分类号:

C39

书目附注:

Includes bibliographical references and index.

内容附注:

Introduction -- Parsing and manipulating structured data -- Exploring texts using the vector space model -- Processing tabular data -- Statistics essentials : who reads novels? -- Introduction to probability -- Narrating with maps -- Stylometry and the voice of Hildegard -- A topic model of United States Supreme Court opinions, 1900-2000 -- Epilogue. Good enough practices.

摘要附注:

"The use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers to discover patterns in a vast range of source materials. Despite this growth, there are few resources addressed to students and scholars who wish to take advantage of these powerful tools. Humanities Data Analysis offers the first intermediate-level guide to quantitative data analysis for humanities students and scholars using the Python programming language. This practical textbook, which assumes a basic knowledge of Python, teaches readers the necessary skills for conducting humanities research in the rapidly developing digital environment. The book begins with an overview of the place of data science in the humanities, and proceeds to cover data carpentry: the essential techniques for gathering, cleaning, representing, and transforming textual and tabular data. Then, drawing from real-world, publicly available data sets that cover a variety of scholarly domains, the book delves into detailed case studies. Focusing on textual data analysis, the authors explore such diverse topics as network analysis, genre theory, onomastics, literacy, author attribution, mapping, stylometry, topic modeling, and time series analysis. Exercises and resources for further reading are provided at the end of each chapter. An ideal resource for humanities students and scholars aiming to take their Python skills to the next level, Humanities Data Analysis illustrates the benefits that quantitative methods can bring to complex research questions. Appropriate for advanced undergraduates, graduate students, and scholars with a basic knowledge of Python. Applicable to many humanities disciplines, including history, literature, and sociology. Offers real-world case studies using publicly available data sets. Provides exercises at the end of each chapter for students to test acquired skills. Emphasizes visual storytelling via data visualizations"--

豆瓣简介：