000			02718nam a22002297a 4500
999			_c4371 _d4371
005			20221216153336.0
008			221216b ||||| |||| 00| 0 eng d
020			_a9780691172361
082			_a005.133 _bKAR
100			_aKarsdorp, Folgert _99560
245			_aHumanities data analysis: _bcase studies with python
260			_bPrinceton University Press _aPrinceton _c2021
300			_axi, 337 p.
365			_aUSD _b45.00
520			_aThe 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
650			_aPython (Computer Program Language) _910951
650			_aHumanities - Research - Methodology _910952
650			_aQuantitative Research - Data Processing _910953
700			_aKestemont, Mike _910954
700			_aRiddell, Allen _910955
942			_2ddc _cBK