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AUTHOR IS RECIPIENT OF THE 2013 AMERICAN ASSOCIATION FOR PUBLIC OPINION RESEARCH AWARD FOR
EXCEPTIONALLY DISTINGUISHED ACHIEVEMENT
SURVEY RESEARCH METHODS FIFTH EDITION
Floyd J. Fowler, Jr., University of Massachusetts Boston
CONTENTS 1. Introduction / 2. Types of Error in Surveys / 3. Sampling / 4. Nonresponse: Implementing a Sample Design / 5. Methods of Data
Collection / 6. Designing Questions to be Good Measures / 7. Evaluating Survey Questions and Instruments / 8. Survey Interviewing / 9. Preparing
Survey Data for Analysis / 10. Analyzing Survey Data / 11. Ethical Issues in Survey Research / 12. Providing Information About Survey Methods / 13.
Survey Error in Perspective
PAPERBACK ISBN: 978-1-4522-5900-0 • ©2014 • 184 PAGES • •
Text Mining
AN INTRODUCTION TO TEXT MINING: Research Design, Data Collection, and
Analysis
Gabe Ignatow, University of North Texas • Rada Mihalcea, University of Michigan
Gabe Ignatow and Rada Mihalcea's An Introduction to Text Mining: Research Design, Data Collection, and Analysis
provides a foundation for readers seeking a solid introduction to mining text data. The book covers the most critical
issues that must be taken into consideration for research projects, including web scraping and crawling, strategic data
selection, data sampling, use of specifi c text analysis methods, and report writing. In addition to covering technical
aspects of various approaches to contemporary text mining and analysis, the book covers ethical and philosophical
dimensions of text-based research and social science research design.
CONTENTS PART I: FOUNDATIONS / 1. Text Mining and Text Analysis / 2. Acquiring Data / 3. Research Ethics / 4. The Philosophy and Logic of
Text Mining / PART II: RESEARCH DESIGN AND BASIC TOOLS / 5. Designing Your Research Project / 6. Web Scraping and Crawling / PART III: TEXT
MINING FUNDAMENTALS / 7. Lexical Resources / 8. Basic Text Processing / 9. Supervised Learning / PART IV: TEXT ANALYSIS METHODS FROM THE
HUMANITIES AND SOCIAL SCIENCES / 10. Analyzing Narratives / 11. Analyzing Themes / 12. Analyzing Metaphors / PART V: TEXT MINING METHODS
FROM COMPUTER SCIENCE / 13. Text Classifi cation / 14.Opinion Mining / 15. Information Extraction / 16. Analyzing Topics / PART VI: WRITING AND
REPORTING YOUR RESEARCH / 17. Writing and Reporting Your Research
PAPERBACK ISBN: 978-1-5063-3700-5 • ©2018 • 344 PAGES •
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resources
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TEXT MINING: A Guidebook for the Social Sciences
Gabe Ignatow, University of North Texas • Rada Mihalcea, University of Michigan
Online communities generate massive volumes of natural language data and the social sciences continue to learn how
to best make use of this new information and the technology available for analyzing it. Text Mining brings together
a broad range of contemporary qualitative and quantitative methods to provide strategic and practical guidance on
analyzing large text collections. This accessible book, written by a sociologist and a computer scientist, surveys the fast-
changing landscape of data sources, programming languages, software packages, and methods of analysis.
CONTENTS PART I: DIGITAL TEXTS, DIGITAL SOCIAL SCIENCE / 1. Social Science and the Digital Text Revolution / 2. Research Design Strategies
/ PART II: TEXT MINING FUNDAMENTALS / 3. Web Crawling and Scraping / 4. Lexical Resources / 5. Basic Text Processing / 6. Supervised
Learning / PART III: TEXT ANALYSIS METHODS FROM THE HUMANITIES AND SOCIAL SCIENCES / 7. Thematic Analysis, QDAS, and Visualization / 8.
Narrative Analysis / 9. Metaphor Analysis / PART IV: TEXT MINING METHODS FROM COMPUTER SCIENCE / 10. Word and Text Relatedness / 11. Text
Classifi cation / 12. Information Extraction / 13. Information Retrieval / 14. Sentiment Analysis / 15. Topic Models / V: CONCLUSIONS / 16. Text
Mining, Text Analysis, and the Future of Social Science
PAPERBACK ISBN: 978-1-4833-6934-1 • ©2017 • 208 PAGES •
online
resources
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