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Author: Claire Lemercier Publisher: University of Virginia Press ISBN: 0813942705 Category : Science Languages : en Pages : 188
Book Description
This timely and lucid guide is intended for students and scholars working on all historical periods and topics in the humanities and social sciences--especially for those who do not think of themselves as experts in quantification, "big data," or "digital humanities." The authors reveal quantification to be a powerful and versatile tool, applicable to a myriad of materials from the past. Their book, accessible to complete beginners, offers detailed advice and practical tips on how to build a dataset from historical sources and how to categorize it according to specific research questions. Drawing on examples from works in social, political, economic, and cultural history, the book guides readers through a wide range of methods, including sampling, cross-tabulations, statistical tests, regression, factor analysis, network analysis, sequence analysis, event history analysis, geographical information systems, text analysis, and visualization. The requirements, advantages, and pitfalls of these techniques are presented in layperson’s terms, avoiding mathematical terminology. Conceived primarily for historians, the book will prove invaluable to other humanists, as well as to social scientists looking for a nontechnical introduction to quantitative methods. Covering the most recent techniques, in addition to others not often enough discussed, the book will also have much to offer to the most seasoned practitioners of quantification.
Author: Claire Lemercier Publisher: University of Virginia Press ISBN: 0813942705 Category : Science Languages : en Pages : 188
Book Description
This timely and lucid guide is intended for students and scholars working on all historical periods and topics in the humanities and social sciences--especially for those who do not think of themselves as experts in quantification, "big data," or "digital humanities." The authors reveal quantification to be a powerful and versatile tool, applicable to a myriad of materials from the past. Their book, accessible to complete beginners, offers detailed advice and practical tips on how to build a dataset from historical sources and how to categorize it according to specific research questions. Drawing on examples from works in social, political, economic, and cultural history, the book guides readers through a wide range of methods, including sampling, cross-tabulations, statistical tests, regression, factor analysis, network analysis, sequence analysis, event history analysis, geographical information systems, text analysis, and visualization. The requirements, advantages, and pitfalls of these techniques are presented in layperson’s terms, avoiding mathematical terminology. Conceived primarily for historians, the book will prove invaluable to other humanists, as well as to social scientists looking for a nontechnical introduction to quantitative methods. Covering the most recent techniques, in addition to others not often enough discussed, the book will also have much to offer to the most seasoned practitioners of quantification.
Author: Arjuna Tuzzi Publisher: Springer ISBN: 331997064X Category : Social Science Languages : en Pages : 217
Book Description
This book demonstrates how quantitative methods for text analysis can successfully combine with qualitative methods in the study of different disciplines of the Humanities and Social Sciences (HSS). The book focuses on learning about the evolution of ideas of HSS disciplines through a distant reading of the contents conveyed by scientific literature, in order to retrieve the most relevant topics being debated over time. Quantitative methods, statistical techniques and software packages are used to identify and study the main subject matters of a discipline from raw textual data, both in the past and today. The book also deals with the concept of quality of life of words and aims to foster a discussion about the life cycle of scientific ideas. Textual data retrieved from large corpora pose interesting challenges for any data analysis method and today represent a growing area of research in many fields. New problems emerge from the growing availability of large databases and new methods are needed to retrieve significant information from those large information sources. This book can be used to explain how quantitative methods can be part of the research instrumentation and the "toolbox" of scholars of Humanities and Social Sciences. The book contains numerous examples and a description of the main methods in use, with references to literature and available software. Most of the chapters of the book have been written in a non-technical language for HSS researchers without mathematical, computer or statistical backgrounds.
Author: Willie van Peer Publisher: John Benjamins Publishing ISBN: 9027274673 Category : Literary Criticism Languages : en Pages : 352
Book Description
Here is a much needed introductory textbook on empirical research methods for the Humanities. Especially aimed at students and scholars of Literature, Applied Linguistics, and Film and Media, it stimulates readers to reflect on the problems and possibilities of testing the empirical assumptions and offers hands-on learning opportunities to develop empirical studies. It explains a wide range of methods, from interviews to observation research, and guides readers through the choices researchers have to make. It discusses the essence of experiments, illustrates how studies are designed, how to develop questionnaires, and helps readers to collect and analyze data by themselves. The book presents qualitative approaches to research but focuses mostly on quantitative methods, detailing the workings of basic statistics. At the end, the book also shows how to give papers at international conferences, how to draft a report, and what is involved in the preparation of a publishable article.
Author: Arjuna Tuzzi Publisher: ISBN: 9783319970653 Category : SOCIAL SCIENCE Languages : en Pages :
Book Description
This book demonstrates how quantitative methods for text analysis can successfully combine with qualitative methods in the study of different disciplines of the Humanities and Social Sciences (HSS). The book focuses on learning about the evolution of ideas of HSS disciplines through a distant reading of the contents conveyed by scientific literature, in order to retrieve the most relevant topics being debated over time. Quantitative methods, statistical techniques and software packages are used to identify and study the main subject matters of a discipline from raw textual data, both in the past and today. The book also deals with the concept of quality of life of words and aims to foster a discussion about the life cycle of scientific ideas. Textual data retrieved from large corpora pose interesting challenges for any data analysis method and today represent a growing area of research in many fields. New problems emerge from the growing availability of large databases and new methods are needed to retrieve significant information from those large information sources. This book can be used to explain how quantitative methods can be part of the research instrumentation and the "toolbox" of scholars of Humanities and Social Sciences. The book contains numerous examples and a description of the main methods in use, with references to literature and available software. Most of the chapters of the book have been written in a non-technical language for HSS researchers without mathematical, computer or statistical backgrounds.--
Author: Taylor Arnold Publisher: Springer ISBN: 3319207024 Category : Computers Languages : en Pages : 211
Book Description
This pioneering book teaches readers to use R within four core analytical areas applicable to the Humanities: networks, text, geospatial data, and images. This book is also designed to be a bridge: between quantitative and qualitative methods, individual and collaborative work, and the humanities and social sciences. Humanities Data with R does not presuppose background programming experience. Early chapters take readers from R set-up to exploratory data analysis (continuous and categorical data, multivariate analysis, and advanced graphics with emphasis on aesthetics and facility). Following this, networks, geospatial data, image data, natural language processing and text analysis each have a dedicated chapter. Each chapter is grounded in examples to move readers beyond the intimidation of adding new tools to their research. Everything is hands-on: networks are explained using U.S. Supreme Court opinions, and low-level NLP methods are applied to short stories by Sir Arthur Conan Doyle. After working through these examples with the provided data, code and book website, readers are prepared to apply new methods to their own work. The open source R programming language, with its myriad packages and popularity within the sciences and social sciences, is particularly well-suited to working with humanities data. R packages are also highlighted in an appendix. This book uses an expanded conception of the forms data may take and the information it represents. The methodology will have wide application in classrooms and self-study for the humanities, but also for use in linguistics, anthropology, and political science. Outside the classroom, this intersection of humanities and computing is particularly relevant for research and new modes of dissemination across archives, museums and libraries.
Author: Folgert Karsdorp Publisher: Princeton University Press ISBN: 0691172366 Category : Computers Languages : en Pages : 352
Book Description
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
Author: lewis levenberg Publisher: Springer ISBN: 3319967134 Category : Social Science Languages : en Pages : 325
Book Description
This volume introduces the reader to the wide range of methods that digital humanities employ, and offers a practical guide to the study, interpretation, and presentation of cultural material and practices. In this instance, the editors consider digital humanities to include both the use of computing to understand cultural material in new ways, and the application of theories and methods from the humanities to interpret new technologies. Each chapter provides a step-by-step guide to cutting-edge methodologies so that students can make informed decisions about the methods they use, consider ethical practices, follow practical procedures, and present their work effectively. Readers will develop practical and reflexive understandings of the software and digital devices that they study and use for research, and the book will help new researchers collaborate and contribute to their scholarly communities, and to public discourse. As contemporary humanities work becomes increasingly interdisciplinary, and increasingly permeated by and with digital technologies, this volume helps new researchers navigate an evolving academic environment. Humanities and social sciences students will find this textbook an invaluable resource for assessing and creating digital projects.
Author: Folgert Karsdorp Publisher: Princeton University Press ISBN: 0691200335 Category : Computers Languages : en Pages : 360
Book Description
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
Author: Kristen Schuster Publisher: Routledge ISBN: 0429670257 Category : Education Languages : en Pages : 678
Book Description
This book draws on both traditional and emerging fields of study to consider consider what a grounded definition of quantitative and qualitative research in the Digital Humanities (DH) might mean; which areas DH can fruitfully draw on in order to foster and develop that understanding; where we can see those methods applied; and what the future directions of research methods in Digital Humanities might look like. Schuster and Dunn map a wide-ranging DH research methodology by drawing on both ‘traditional’ fields of DH study such as text, historical sources, museums and manuscripts, and innovative areas in research production, such as knowledge and technology, digital culture and society and history of network technologies. Featuring global contributions from scholars in the United Kingdom, the United States, Europe and Australia, this book draws together a range of disciplinary perspectives to explore the exciting developments offered by this fast-evolving field. Routledge International Handbook of Research Methods in Digital Humanities is essential reading for anyone who teaches, researches or studies Digital Humanities or related subjects.
Author: Claire Lemercier
Author: Claire Lemercier
Author: Arjuna Tuzzi
Author: Willie van Peer
Author: Arjuna Tuzzi
Author: Taylor Arnold
Author: Folgert Karsdorp
Author: Rajesh Ekka
Author: lewis levenberg
Author: Folgert Karsdorp
Author: Kristen Schuster