Text mining : a guidebook for the social sciences /: a guidebook for the social sciences. (2016)

• Record Type: Book
• Further Information: Note: Gabe Ignatow, University of North Texas, Rada Mihalcea, University of Michigan.
• Authors: Ignatow, Gabe; Radev, Dragomir, 1968-
• Contents: Part I: Digital Texts, Digital Social Science; 1. Social Science and the Digital Text Revolution; Learning Objectives; Introduction; History of Text Analysis; Risk and Rewards of Text Mining for the Social Sciences; Social Data from Digital Environments; Theory and Metatheory; Ethics of Text Mining; Organization of This Volume; 2. Research Design Strategies; Learning Objectives; Introduction; Levels of Analysis; Strategies for Document Selection and Sampling; Types of Inferential Logic; Approaches to Research Design; Part II: Text Mining Fundamentals; 3. Web Crawling and Scraping; Learning Objectives; Introduction; Web Statistics; Web Crawling; Web Scraping; Software for Web Crawling and Scraping; 4. Lexical Resources; Learning Objectives; Introduction; WordNet; Roget's Thesaurus; Linguistic Inquiry and Word Count; General Inquirer; Wikipedia; Downloadable Lexical Resources and APIs; 5. Basic Text Processing; Learning Objectives; Introduction; Tokenization; Stopword Removal; Stemming and Lemmatization; Text Statistics; Language Models; Other Text Processing; Software for Text Processing; 6. Supervised Learning; Learning Objectives; 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; Learning Objectives; Thematic Analysis; Qualitative Data Analysis Software; Visualization Tools; 8. Narrative Analysis; Learning Objectives; Introduction; Conceptual Foundations; Mixed Methods of Narrative Analysis; Automated Approaches to Narrative Analysis; Future Directions; Specialized Software for Narrative Analysis; 9. Metaphor Analysis; Learning Objectives; Introduction; Theoretical Foundations; 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; Learning Objectives; Introduction; Theoretical Foundations; Corpus-based and Knowledge-based Measures of Relatedness; Software and Datasets for Word and Text Relatedness; Further Reading; 11. Text Classification; Learning Objectives; Introduction; 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; Learning Objectives; Introduction; Entity Extraction; Relation Extraction; Web Information Extraction; Template Filling; Software and Datasets for Information Extraction and Text Mining; 13. Information Retrieval; Learning Objectives; Introduction; Theoretical Foundations; Components of an Information Retrieval System; Information Retrieval Models; The Vector-Space Model; Evaluation of Information Retrieval Models; Web-Based Information Retrieval; Software and Datasets for Information Retrieval; 14. Sentiment Analysis; Learning Objectives; Introduction; Theoretical Foundations; Lexicons; Corpora; Tools; Future Directions; Software and Datasets for Word and Text Relatedness; 15. Topic Models; Learning Objectives; Introduction; Digital Humanities; Political Science; Sociology; Software for Topic Modeling; V: Conclusions; 16. Text Mining, Text Analysis, and the Future of Social Science; Introduction; Social and Computer Science Collaboration;
• Publisher Details: Thousand Oaks : SAGE Publications, Inc
• Publication Date: 2016
• Extent: 1 online resource (208 pages)
• Subjects: 300.72/1; Social sciences -- Research -- Methodology; Discourse analysis -- Data processing; Communication -- Network analsysis; Natural language processing (Computer science); Data mining
• Languages: English
• ISBNs: 9781483369327; 1483369323
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.