Text mining: a guidebook for the social sciences
By: Ignatow, Gabe
Contributor(s): Mihalcea, Rada
Material type: 
TextPublisher: Thousand Oaks Sage Publications 2017Description: xvi, 188 p.ISBN: 9781483369341Subject(s): Research Methodology - Social science | Discourse analysis - Data processing | Communication - Network analsysis | Natural Language Processing - Computer science | Data MiningDDC classification: 300.721 Summary: 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.
https://in.sagepub.com/en-in/sas/text-mining/book244124
| Item type | Current location | Item location | Collection | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|---|
| Books | Vikram Sarabhai Library General Stacks | Slot 232 (0 Floor, West Wing) | Non-fiction | 300.721 I4T3 (Browse shelf) | Checked out | 04/09/2021 | 193664 |
Table of Contents:
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
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.
https://in.sagepub.com/en-in/sas/text-mining/book244124
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