TY  - BOOK
AU  - Ignatow,Gabriel
AU  - Mihalcea,Rada
TI  - Text mining: a guidebook for the social sciences 
SN  - 148336934X
AV  - H61.3 .I395 2017
U1  - 300.721 23
PY  - 2017///]
CY  - Los Angeles
PB  - SAGE
KW  - Social sciences
KW  - Research
KW  - Methodology
KW  - Discourse analysis
KW  - Data processing
KW  - Natural language processing (Computer science)
KW  - Data mining
N1  - Includes bibliographical references and index; Part I: Digital Texts, Digital Social Science -- 1. Social Science and the Digital Text Revolution -- 2. Research Design Strategies -- Part II: Text Mining Fundamentals -- 3. Web Crawling and Scraping -- 4. Lexical Resources -- 5. Basic Text Processing -- 6. Supervised Learning -- Part III: Text Analysis Methods from the Humanities and Social Sciences -- 7. Thematic Analysis, QDAS, and Visualization -- 8. Narrative Analysis -- 9. Metaphor Analysis -- Part IV: Text Mining Methods from Computer Science -- 10. Word and Text Relatedness -- 11. Text Classification -- 12. Information Extraction -- 13. Information Retrieval -- 14. Sentiment Analysis -- 15. Topic Models -- Part V: Conclusions -- 16. Text Mining, Text Analysis, and the Future of Social Science
N2  - "Online communities generate massive volumes of natural language data and the social sciences continue to learn how to best make use of this new information and the technology available for analyzing it. Text Mining brings together a broad range of contemporary qualitative and quantitative methods to provide strategic and practical guidance on analyzing large text collections. This accessible book, written by a sociologist and a computer scientist, surveys the fast-changing landscape of data sources, programming languages, software packages, and methods of analysis available today. Suitable for novice and experienced researchers alike, the book will help readers use text mining techniques more efficiently and productively." --Publisher's website
ER  -