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Author : Rajesh Ekka
Publisher : Lulu.com
Page : 102 pages
File Size : 34,72 MB
Release : 2014-12-16
Category : Education
ISBN : 1312760125
Research refers to a search for knowledge. Research is an art of scientific investigation. The Advanced Learner's Dictionary of Current English lays down the meaning of research as, "a careful investigation or inquiry especially through search for new facts in any branch of knowledge".
Author : Folgert Karsdorp
Publisher : Princeton University Press
Page : 352 pages
File Size : 47,33 MB
Release : 2021-01-12
Category : Computers
ISBN : 0691172366
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 : Anol Bhattacherjee
Publisher : CreateSpace
Page : 156 pages
File Size : 38,83 MB
Release : 2012-04-01
Category : Science
ISBN : 9781475146127
This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.
Author : Taylor Arnold
Publisher : Springer
Page : 218 pages
File Size : 30,27 MB
Release : 2015-09-23
Category : Computers
ISBN : 3319207024
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 : Rajat Acharyya
Publisher : Taylor & Francis
Page : 229 pages
File Size : 47,78 MB
Release : 2019-11-01
Category : Social Science
ISBN : 1000725782
Research Methodology for Social Sciences provides guidelines for designing and conducting evidence-based research in social sciences and interdisciplinary studies using both qualitative and quantitative data. Blending the particularity of different sub-disciplines and interdisciplinary nature of social sciences, this volume: Provides insights on epistemological issues and deliberates on debates over qualitative research methods; Covers different aspects of qualitative research techniques and evidence-based research techniques, including survey design, choice of sample, construction of indices, statistical inferences and data analysis; Discusses concepts, techniques and tools at different stages of research, beginning with the design of field surveys to collect raw data and then analyse it using statistical and econometric methods. With illustrations, examples and a reader-friendly approach, this volume will serve as a key reference material for compulsory research methodology courses at doctoral levels across different disciplines, such as economics, sociology, women’s studies, education, anthropology, political science, international relations, philosophy, history and business management. This volume will also be indispensable for postgraduate courses dealing with quantitative techniques and data analysis.
Author : Folgert Karsdorp
Publisher : Princeton University Press
Page : 360 pages
File Size : 24,68 MB
Release : 2021-01-12
Category : Computers
ISBN : 0691200335
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 : Thanh V. Tran
Publisher :
Page : 340 pages
File Size : 24,93 MB
Release : 2016-08-09
Category : Social Science
ISBN : 9781516553235
Research Methods & Data Analysis for Multicultural Social Work and Human Services introduces research methodology to social work students and practitioners. It provides hands-on examples of how to conduct data analysis in SPSS and Stata. It equips readers with the skills needed to become critical research consumers and to engage in agency-based research and evaluation. The text teaches students how to collect appropriate data and analyze data that is suitable for each type of research design. It prepares them to conduct applied social science research in a variety of fields, such as health and mental health, ethnic studies, acculturation, family violence, LGBT studies, and more. Topics addressed include the process of research, ethical issues, the validity and reliability of research instruments, design types, and relevant statistical tools. Research Methods & Data Analysis for Multicultural Social Work and Human Services provides a solid foundation and knowledge base for students and researchers. It is an excellent resource for undergraduate and graduate level research methods and design classes and courses on research and statistics in social work. Thanh V. Tran holds a Ph.D. and a master of science degree in social work from the School of Social Work at the University of Texas, Arlington. Dr. Tran is a professor in the Boston College School of Social Work in Chestnut Hill, Massachusetts. Ce Shen earned a Ph.D. in sociology at Boston College in Chestnut Hill and is now an associate professor in the college's School of Social Work. Siyon Rhee earned a Ph.D. at the School of Social Welfare, University of California, Los Angeles. Dr. Rhee teaches in the School of Social Work at California State University, Los Angeles.
Author : Arvind Kumar
Publisher : Sarup & Sons
Page : 376 pages
File Size : 20,22 MB
Release : 2002
Category : Social sciences
ISBN : 9788176252782
Yet Research May Be Regarded As A Useful Form Of Activity. Research, In The Sense Of Development, Elaboration And Refinement Of Principles, Together With The Collection And Use Of Empirical Materials To Help In These Processes, Is One Of Die Highest Activities Of A University And One In Which All Its Professors Should Be Engaged. Research Need Not Be Thought Of As A Special Prerogative Of Young Men And Women Preparing Themselves For A Higher Degree. Nobody Needs The Permission Of A University To Do Research And Many Of The Great Scholars Did Not Any Research In The Ordinary Sense Of The Term. Yet They Succeeded In Contributing Significantly To The Existing Realms Of Knowledge. Research Is A Matter Of Realising A Question And Then Trying To Find An Answer. In Other Words, Research Means A Sort Of Investigation Describing The Fact That Some Problem Is Being Investigated To Shed For Generalization. Therefore, Research Is The Activity Of Solving Problem Which Adds New Knowledge And Developing Of Theory As Well As Gathering Of Evidence To Test Generalization.In View Of This, The Present Attempt Is Made To Describe The Different Aspects Of Research Generally Being Conducted By The Social Scientists And It Is Hoped That It Will Be Of Great Use For All Those Concerned With Social Research.
Author : Arjuna Tuzzi
Publisher : Springer
Page : 217 pages
File Size : 35,7 MB
Release : 2018-10-30
Category : Social Science
ISBN : 331997064X
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 : Claire Lemercier
Publisher :
Page : 188 pages
File Size : 46,89 MB
Release : 2019
Category : History
ISBN : 9780813942698
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.