An Introduction to Text Mining Research Design Data Collection and Analysis

367 Pages·2018·4.15 MB·English

by  Gabe Ignatow

An Introduction to Text Mining

An Introduction to Text Mining
Research Design, Data Collection, and Analysis
Gabe Ignatow
University of North Texas
Rada Mihalcea
University of Michigan
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Printed in the United States of America Library of Congress Cataloging-in-
Publication Data
Names: Ignatow, Gabe, author. | Mihalcea, Rada, 1974-author.
Title: An introduction to text mining : research design, data collection, and
analysis / Gabe Ignatow, University of North Texas, Rada Mihalcea, University
of Michigan.
Description: Thousand Oaks : SAGE Publications, [2018] | Includes
bibliographical references and index.
Identifiers: LCCN 2017038203 | ISBN 9781506337005 (pbk. : alk. paper)
Subjects: LCSH: Data mining. | Social sciences—Research.
Classification: LCC QA76.9.D343 I425 2017 | DDC 006.3/12—dc23 LC record
available at https://lccn.loc.gov/2017038203
This book is printed on acid-free paper.
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Brief Contents
Acknowledgments
Preface
About the Authors
PART I ∎ FOUNDATIONS
∎ Chapter 1 Text Mining and Text Analysis
∎ Chapter 2 Acquiring Data
∎ Chapter 3 Research Ethics
∎ Chapter 4 The Philosophy and Logic of Text Mining
PART II ∎ RESEARCH DESIGN AND BASIC TOOLS
∎ Chapter 5 Designing Your Research Project
∎ Chapter 6 Web Scraping and Crawling
PART III ∎ TEXT MINING FUNDAMENTALS
∎ Chapter 7 Lexical Resources
∎ Chapter 8 Basic Text Processing
∎ Chapter 9 Supervised Learning
PART IV ∎ TEXT ANALYSIS METHODS FROM THE
HUMANITIES AND SOCIAL SCIENCES
∎ Chapter 10 Analyzing Narratives
∎ Chapter 11 Analyzing Themes
∎ Chapter 12 Analyzing Metaphors
PART V ∎ TEXT MINING METHODS FROM COMPUTER
SCIENCE
∎ Chapter 13 Text Classification
∎ Chapter 14 Opinion Mining
∎ Chapter 15 Information Extraction
∎ Chapter 16 Analyzing Topics
PART VI ∎ WRITING AND REPORTING YOUR RESEARCH
∎ Chapter 17 Writing and Reporting Your Research
Appendix A. Data Sources for Text Mining
Appendix B. Text Preparation and Cleaning Software
Appendix C. General Text Analysis Software
Appendix D. Qualitative Data Analysis Software
Appendix E. Opinion Mining Software
Appendix F. Concordance and Keyword Frequency Software
Appendix G. Visualization Software
Appendix H. List of Websites
Appendix I. Statistical Tools
Glossary
References
Index
Detailed Contents
Acknowledgments
Preface
Note to the Reader
About the Authors
PART I ∎ FOUNDATIONS
∎ Chapter 1 Text Mining and Text Analysis
Learning Objectives
Introduction
Six Approaches to Text Analysis
Conversation Analysis
Analysis of Discourse Positions
Critical Discourse Analysis
Content Analysis
Foucauldian Analysis
Analysis of Texts as Social Information
Challenges and Limitations of Using Online Data
Social Surveys
Ethnography
Historical Research Methods
Conclusion
Key Terms
Highlights
Review Questions
Discussion Questions
Developing a Research Proposal
Further Reading
∎ Chapter 2 Acquiring Data
Learning Objectives
Introduction
Online Data Sources
Advantages and Limitations of Online Digital Resources for
Social Science Research
Examples of Social Science Research Using Digital Data
Conclusion
Key Term
Highlights
Discussion Questions
∎ Chapter 3 Research Ethics
Learning Objectives
Introduction
Respect for Persons, Beneficence, and Justice
Ethical Guidelines
Institutional Review Boards
Privacy
Informed Consent
Manipulation
Publishing Ethics
Scenario 1
Scenario 2
Scenario 3
Conclusion
Key Terms
Highlights
Review Questions
Discussion Questions
Web Resources
Developing a Research Proposal
Further Reading
∎ Chapter 4 The Philosophy and Logic of Text Mining
Learning Objectives
Introduction
Ontological and Epistemological Positions
Correspondence Theory
Coherence Theory
Pragmatism
Constructionism
Critical Realism
Metatheory
Grand Theory and Philosophical Positions
Meso Theory
Models
Substantive Theory
Making Inferences
Inductive Logic
Deductive Logic
Abductive Logic