An Introduction to Text Mining Research Design Data Collection and Analysis

Description

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project based on online sources of textual data such as newspaper archives, site user comment archives, digitized historical documents, or social media user comment archives.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. Chapter 1. Text Mining and Text Analysis Chapter 2. Acquiring Data Chapter 3. Research Ethics Chapter 4. The Philosophy and Logic of Text Mining Chapter 5. Designing Your Research Project Chapter 6. Web Scraping and Crawling Chapter 7. Lexical Resources Chapter 8. Basic Text Processing Chapter 9. Supervised Learning Chapter 10. Analyzing Narratives Chapter 11. Analyzing Themes Chapter 12. Analyzing Metaphors Chapter 13. Text Classification Chapter 14. Opinion Mining Chapter 15. Information Extraction Chapter 16. Analyzing Topics 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