Part I: Digital Texts, Digital Social Science
1. Social Science and the Digital Text Revolution
Risk and Rewards of Text Mining for the Social Sciences
Social Data from Digital Environments
Organization of This Volume
2. Research Design Strategies
Strategies for Document Selection and Sampling
Types of Inferential Logic
Approaches to Research Design
Part II: Text Mining Fundamentals
3. Web Crawling and Scraping
Software for Web Crawling and Scraping
4. Lexical Resources
Linguistic Inquiry and Word Count
Downloadable Lexical Resources and APIs
5. Basic Text Processing
Stemming and Lemmatization
Software for Text Processing
6. Supervised Learning
Feature Representation and Weighting
Supervised Learning Algorithms
Evaluation of Supervised Learning
Software for Supervised Learning
Part III: Text Analysis Methods from the Humanities and Social Sciences
7. Thematic Analysis, QDAS, and Visualization
Qualitative Data Analysis Software
8. Narrative Analysis
Mixed Methods of Narrative Analysis
Automated Approaches to Narrative Analysis
Specialized Software for Narrative Analysis
9. Metaphor Analysis
Qualitative Metaphor Analysis
Mixed Methods of Metaphor Analysis
Automated Metaphor Identification Methods
Software for Metaphor Analysis
Part IV: Text Mining Methods from Computer Science
10. Word and Text Relatedness
Corpus-based and Knowledge-based Measures of Relatedness
Software and Datasets for Word and Text Relatedness
11. Text Classification
Applications of Text Classification
Representing Texts for Supervised Text Classification
Text Classification Algorithms
Bootstrapping in Text Classifcation
Evaluation of Text Classification
Software and Datasets for Text Classification
12. Information Extraction
Web Information Extraction
Software and Datasets for Information Extraction and Text Mining
13. Information Retrieval
Components of an Information Retrieval System
Information Retrieval Models
Evaluation of Information Retrieval Models
Web-Based Information Retrieval
Software and Datasets for Information Retrieval
14. Sentiment Analysis
Software and Datasets for Word and Text Relatedness
15. Topic Models
Software for Topic Modeling
V: Conclusions
16. Text Mining, Text Analysis, and the Future of Social Science
Social and Computer Science Collaboration