Gabe Ignatow & Rada F. Mihalcea 
An Introduction to Text Mining [EPUB ebook] 
Research Design, Data Collection, and Analysis

This is the ideal introduction for students seeking to collect and analyze textual data from online sources. It covers the most critical issues that they must take into consideration at all stages of their research projects.

قائمة المحتويات

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

Challenges and Limitations of Using Online Data

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

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

Metatheory

Making Inferences

Conclusion

Key Terms

Highlights

Discussion Questions

Internet Resources

Developing a Research Proposal

Further Reading

PART II. RESEARCH DESIGN AND BASIC TOOLS

Chapter 5. Designing Your Research Project

Learning Objectives

Introduction

Critical Decisions

Idiographic and Nomothetic Research

Levels of Analysis

Qualitative, Quantitative, and Mixed Methods Research

Choosing Data

Formatting Your Data

Conclusion

Key Terms

Highlights

Review Questions

Discussion Questions

Developing a Research Proposal

Further Reading

Chapter 6. Web Scraping and Crawling

Learning Objectives

Introduction

Web Statistics

Web Crawling

Web Scraping

Software for Web Crawling and Scraping

Conclusion

Key Terms

Highlights

Discussion Questions

PART III. TEXT MINING FUNDAMENTALS

Chapter 7. Lexical Resources

Learning Objectives

Introduction

Word Net

Roget’s Thesaurus

Linguistic Inquiry and Word Count

General Inquirer

Wikipedia

Conclusion

Key Terms

Highlights

Discussion Topics

Chapter 8. Basic Text Processing

Learning Objectives

Introduction

Basic Text Processing

Language Models and Text Statistics

More Advanced Text Processing

Conclusion

Key Terms

Highlights

Discussion Topics

Chapter 9. Supervised Learning

Learning Objectives

Introduction

Feature Representation and Weighting

Supervised Learning Algorithms

Evaluation of Supervised Learning

Conclusion

Key Terms

Highlights

Discussion Topics

PART IV. TEXT ANALYSIS METHODS FROM THE HUMANITIES AND SOCIAL SCIENCES

Chapter 10. Analyzing Narratives

Learning Objectives

Introduction

Approaches to Narrative Analysis

Planning a Narrative Analysis Research Project

Qualitative Narrative Analysis

Mixed Methods and Quantitative Narrative Analysis Studies

Conclusion

Key Terms

Highlights

Review Questions

Developing a Research Proposal

Further Reading

Chapter 11. Analyzing Themes

Learning Objectives

Introduction

How to Analyze Themes

Examples of Thematic Analysis

Conclusion

Key Terms

Highlights

Review Questions

Developing a Research Proposal

Further Reading

Chapter 12. Analyzing Metaphors

Learning Objectives

Introduction

Cognitive Metaphor Theory

Approaches to Metaphor Analysis

Qualitative, Quantitative, and Mixed Methods

Conclusion

Key Terms

Highlights

Review Questions

Developing a Research Proposal

Further Reading

PART V. TEXT MINING METHODS FROM COMPUTER SCIENCE

Chapter 13. Text Classification

Learning Objectives

Introduction

What Is Text Classification?

Applications of Text Classification

Approaches to Text Classification

Conclusion

Key Terms

Highlights

Discussion Topics

Chapter 14. Opinion Mining

Learning Objectives

Introduction

What Is Opinion Mining?

Resources for Opinion Mining

Approaches to Opinion Mining

Conclusion

Key Terms

Highlights

Discussion Topics

Chapter 15. Information Extraction

Learning Objectives

Introduction

Entity Extraction

Relation Extraction

Web Information Extraction

Template Filling

Conclusion

Key Terms

Highlights

Discussion Topics

Chapter 16. Analyzing Topics

Learning Objectives

Introduction

What Are Topic Models?

How to Use Topic Models

Examples of Topic Modeling

Conclusion

Key Terms

Highlights

Review Questions

Developing a Research Proposal

Internet Resources

Further Reading

PART VI. WRITING AND REPORTING YOUR RESEARCH

Chapter 17. Writing and Reporting Your Research

Learning Objectives

Introduction: Academic Writing

Evidence and Theory

The Structure of Social Science Research Papers

Conclusion

Key Terms

Highlights

Web Resources

Undergraduate Research Journals

Further Reading

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

عن المؤلف

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.