Humanities Data Analysis
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Humanities Data Analysis: Case Studies with Python

Humanities Data Analysis: Case Studies with Python


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About the Book

A practical guide to data-intensive humanities research using the Python programming language 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

About the Author :
Folgert Karsdorp is a postdoctoral researcher at the Meertens Institute of the Royal Netherlands Academy of Arts and Sciences. Mike Kestemont is assistant professor of literature at the University of Antwerp. Twitter @Mike_Kestemont Allen Riddell is assistant professor of information science at Indiana University.

Review :
"Humanities Data Analysis is a much-welcome addition to the texts available for teaching programming and the digital humanities in college and university classrooms."--Brad Pasanek, University of Virginia "Humanities Data Analysis provides readers with a theoretical perspective on a range of powerful methods as well as practical example code in Python to get started on new projects. What sets this book truly apart is how every chapter acts as a little detective story, motivated by compelling, complicated, real-data examples that will resonate with students."--David Mimno, Cornell University "Guiding readers through substantive case studies in data analysis, this impressive and unique textbook is a great gift to the humanities and social sciences, not only to undergraduate and graduate students but to scholars at all proficiency levels. It provides a standard for meaningful computational analysis against which other textbooks and scholarship will be measured."--Andrew Goldstone, Rutgers University "This book will be a great help to humanities students and scholars learning to use digital data. The authors carefully explain different methods for exploring and analyzing the data, and they unpack formulas in a wonderfully transparent way. Humanities Data Analysis will educate and inspire a multitude of new digital humanists as well as those already working in the field."--Karina van Dalen-Oskam, Huygens Institute and University of Amsterdam "This is an excellent introduction to a set of methods and approaches to doing computational text analysis. It will be an invaluable resource in helping humanists develop computational literacy for working with data in Python."--Trevor Owens, American University "Armed with this textbook, students coming to the digital humanities have a new and valuable tool to easily acquire necessary computational skills. This book gives readers practical expertise and a solid knowledge of the methods involved, and strengthens their capacity for solving common problems in humanities data analysis."--Iza Romanowska, Aarhus Institute of Advanced Studies


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Product Details
  • ISBN-13: 9780691200330
  • Publisher: Princeton University Press
  • Publisher Imprint: Princeton University Press
  • Edition: School edition
  • Sub Title: Case Studies with Python
  • ISBN-10: 0691200335
  • Publisher Date: 12 Jan 2021
  • Binding: Digital (delivered electronically)
  • Language: English


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