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

An Introduction to Text Mining: Research Design, Data Collection, and Analysis By 作者: Gabe Ignatow – Rada F. Mihalcea ISBN-10 书号: 1506337007 ISBN-13 书号: 9781506337005 Edition 版本: 1 出版日期: 2017-10-25 pages 页数: (344 ) 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project based on online sources of textual data such as newspaper archives, site user comment archives, digitized historical documents, or social media user comment archives.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. Coper Half Title Publisher Finelybook 出版社 Note Title Page Copyright Page Brief Contents Detailed Contents Acknowlednents Preface Note to the Reader About the Authors 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 Desin and Basic Tools 5 Desi ning Your Research Project 6Web 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 lMetaphors Part V Text Mining Methods From Computer Science 13 Text Classification 140pinion Mining 15 Information Extraction 16 Analyzing Topics Part VI Writing and Reporting Your Research 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