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Informationen zum Autor Gabe Ignatow is Professor of Sociology and Director of Graduate Studies at the University of North Texas. His research interests are mainly in the areas of sociological theory, digital research methods, cognitive social science, and the philosophy of social science. His most recent books are Text Mining and An Introduction to Text Mining , both coauthored with Rada Mihalcea (University of Michigan). He is also a coeditor, with Wayne Brekhus (University of Missouri), of the Oxford Handbook of Cognitive Sociology . Rada Mihalcea is a professor of computer science and engineering at the University of Michigan. Her research interests are in computational linguistics, with a focus on lexical semantics, multilingual natural language processing, and computational social sciences. She serves or has served on the editorial boards of the following journals: Computational Linguistics , Language Resources and Evaluation , Natural Language Engineering, Research on Language and Computation , IEEE Transactions on Affective Computing , and Transactions of the Association for Computational Linguistics . She was a general chair for the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL, 2015) and a program cochair for the Conference of the Association for Computational Linguistics (2011) and the Conference on Empirical Methods in Natural Language Processing (2009). She is the recipient of a National Science Foundation CAREER award (2008) and a Presidential Early Career Award for Scientists and Engineers (2009). In 2013, she was made an honorary citizen of her hometown of Cluj-Napoca, Romania. Klappentext 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 Zusammenfassung This practical book provides researchers strategic and practical guidance on using text mining methods to analyze large text collections more efficiently and productively. Inhaltsverzeichnis 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...
