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An Introduction to Text Mining: Research Design, Data Collection, and Analysis

An Introduction to Text Mining: Research Design, Data Collection, and Analysis

by Gabe Ignatow (Author), Rada F. Mihalcea (Author)

  • New

    Paperback 2017

    $123.86
Synopsis

Students in social science courses communicate, socialize, shop, learn, and work online. When they are asked to collect data for course projects they are often drawn to social media platforms and other online sources of textual data. There are many software packages and programming languages available to help students collect data online, and there are many texts designed to help with different forms of online research, from surveys to ethnographic interviews. But there is no textbook available that teaches students how to construct a viable research project based on online sources of textual data such as newspaper archives, site user comment archives, digitized historical documents, or social media user comment archives. Gabe Ignatow and Rada F. Mihalcea's new text An Introduction to Text Mining will be a starting point for undergraduates and first-year graduate students interested in collecting and analyzing textual data from online sources, and will cover the most critical issues that students must take into consideration at all stages of their research projects, including: ethical and philosophical issues; issues related to research design; web scraping and crawling; strategic data selection; data sampling; use of specific text analysis methods; and report writing.

$123.86

Quantity

20+ in stock

More Information

Format: Paperback
 Pages: 346
 Edition: 1
 Publisher: SAGE Publications, Inc
Published: 11 Oct 2017
ISBN 10: 1506337007
ISBN 13: 9781506337005

Media Reviews

This is a comprehensive book on a timely and important research method for social scientific research. Researchers who want to learn the development of text mining methods and learn how to integrate the methods into their research projects will find this book beneficial.

-- Kenneth C. C. Yang

In the age of big data, this text is an excellent introduction to text mining for undergraduates and beginning graduate students. The proliferation of text as data particularly in social media require the inclusion of this topic in the data analysis toolkit of the social scientist.

-- A. Victor Ferreros

This is an excellent book that covers a broad range of topics on text analysis. Examples from a variety of disciplines are used, making the text useful to students across the social sciences, humanities, and sciences and also accessible to those who do not have a deep background in this area.

-- Jennifer Bachner

This book provides an excellent base for budding data scientists and provides tools, methods and references that will be extremely useful in their work. Methods from various disciplines are discussed in detail and provide a wonderful base for building business appropriate data mining projects.

-- Roger D. Clark
Author Bio
Gabe Ignatow is an Associate Professor of Sociology at the University of North Texas where he has taught since 2007. His research interests are in the areas of sociological theory, text mining and analysis methods, new media, and information policy. Gabe's current research involves working with computer scientists and statisticians to adapt text mining and topic modeling techniques for social science applications. Gabe has been working with mixed methods of text analysis since the 1990s, and has published this work in journals including Social Forces, Sociological Forum, Poetics, the Journal for the Theory of Social Behaviour, and the Journal of Computer-Mediated Communication. He is the author of over 30 peer-reviewed articles and book chapters and serves on the editorial boards of the journals Sociological Forum, the Journal for the Theory of Social Behaviour, and Studies in Media and Communications. He has served as the UNT Department of Sociology's graduate program co-director and undergraduate program director and has been selected as a faculty fellow at the Center for Cultural Sociology at Yale University. He is also a co-founder and the CEO of GradTrek, a graduate degree search engine company. Rada Mihalcea is a professor of computer science and engineering at the University of Michigan. Her research interests are in computational linguistics, with a focus on lexical semantics, multilingual natural language processing, and computational social sciences. She serves or has served on the editorial boards of the following journals: Computational Linguistics, Language Resources and Evaluation, Natural Language Engineering, Research on Language and Computation, IEEE Transactions on Affective Computing, and Transactions of the Association for Computational Linguistics. She was a general chair for the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL, 2015) and a program cochair for the Conference of the Association for Computational Linguistics (2011) and the Conference on Empirical Methods in Natural Language Processing (2009). She is the recipient of a National Science Foundation CAREER award (2008) and a Presidential Early Career Award for Scientists and Engineers (2009). In 2013, she was made an honorary citizen of her hometown of Cluj-Napoca, Romania.