An Introduction to Text Mining: Research Design, Data Collection, and Analysis
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资源说明: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project based on online sources of textual data such as newspaper archives, site user comment archives, digitized historical documents, or social media user comment archives.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
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