Text Analysis for the Social Sciences: Methods for Drawing Statistical Inferences from Texts and Transcripts

Text Analysis for the Social Sciences: Methods for Drawing Statistical Inferences from Texts and Transcripts

Text Analysis for the Social Sciences: Methods for Drawing Statistical Inferences from Texts and Transcripts

Text Analysis for the Social Sciences: Methods for Drawing Statistical Inferences from Texts and Transcripts

Synopsis

This book provides descriptions and illustrations of cutting-edge text analysis methods for communication and marketing research; cultural, historical-comparative, and event analysis; curriculum evaluation; psychological diagnosis; language development research; and for any research in which statistical inferences are drawn from samples of texts. Although the book is accessible to readers having no experience with content analysis, the text analysis expert will find substantial new material in its pages. In particular, this collection describes developments in semantic and network text analysis methodologies that heretofore have been accessible only among a smattering of methodology journals. The book's international and cross-disciplinary content illustrates the breadth of quantitative text analysis applications. These applications demonstrate the methods' utility for international research, as well as for practitioners from the fields of sociology, political science, journalism/communication, computer science, marketing, education, and English. This is an "ecumenical" collection that contains applications not only of the most recent semantic and network text analysis methods, but also of the more traditional thematic method of text analysis. In fact, it is originally with this volume that these two "relational" approaches to text analysis are defined and contrasted with more traditional "thematic" text analysis methods. The emphasis here is on application. The book's chapters provide guidance regarding the sorts of inferences that each method affords, and up-to-date descriptions of the human and technological resources required to apply the methods. Its purpose is as a resource for making quantitative text analysis methods more accessible to social science researchers.

Excerpt

Carl W. Roberts Iowa State University

This book is for social science researchers with research questions applicable to relatively well-defined populations of texts. Although the book is accessible to readers having no experience with content analysis, the text analysis expert will find much new in its pages. In particular, this collection describes developments in semantic and network text analysis methodologies that heretofore have been accessible only among a smattering of methodology journals. In fact, it is originally with this volume that these two relational approaches to text analysis are defined and contrasted with more traditional, thematic text analysis methods. The emphasis here is on application. That is, this book's purpose is as an aid in answering the question, "Which text analysis method best affords answers to what research questions?"

Shapiro and Markoff's chapter introduces the reader to classical issues in content analysis methodology (e.g., the primacy of manifest vs. latent content, the requisites of scientific rigor, etc.). The authors develop a minimal definition of content analysis-a definition that encompasses methodologies far beyond the purview of this text. Whereas text analyses are only of texts or transcripts, content analyses can be performed on any symbolic material, be it visual, acoustic, tactile, or whatever. Beyond its limitation to texts, the domain of this book is also restricted to quantitative text analysis methods.

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