textmapping.com Open in urlscan Pro
35.185.44.232  Public Scan

Form analysis
0 forms found in the DOM

Text Content

MAPPING TEXTS



 * 
 * 

 * © 2020-2024
 * imprint

 * Home

Mapping Texts is the first introduction to computational text analysis that
simultaneously blends conceptual treatments with practical, hands-on examples
that walk the reader through how to conduct text analysis projects with real
data and code. The book shows how to conduct text analysis in the R statistical
computing environment – a popular programming language in data science.

--------------------------------------------------------------------------------


PREORDER

OxfordPowell'sBookshop.orgThriftbooksBarnes & NobleAmazon


ADVANCE PRAISE

> “ Stoltz and Taylor have managed to create a work that confidently takes even
> a beginner to a position of sophistication and technical virtuosity, leading
> to not only a practical mastery of cutting edge techniques, nor just that plus
> a clear understanding of the mathematical bases, but also gives the reader an
> intuitive feel for the larger social contexts that produce the text data
> analyzed... and all this without dropping a single equation in the reader's
> lap!  A true gem.

— John Levi Martin, Florence Borchert Bartling Professor of Sociology at The
University of Chicago and author of Thinking Through Methods

> “ Language is pragmatic, language is habitual, language is relational. I have
> been waiting for a book like this. One that seamlessly integrates philosophy
> and theory with tools and reproducible examples, and does so in a deeply
> sociological way. If you read this book, if you teach with this book, you and
> your students will have everything needed to successfully do computational
> text analysis in the social sciences. An extraordinary contribution.

— Laura K. Nelson, Assistant Professor of Sociology at The University of British
Columbia

> “ Packed with interesting examples, Mapping Texts reveals the exciting
> possibilities of computational text analysis for social science.  It’s one of
> those rare books that offers useful advice about both what to do and how to do
> it. I think many readers will love Stoltz and Taylor’s decision to use no
> equations and illustrate key ideas with code in R. Mapping Text will be
> helpful to anyone hoping to learn more about this dynamic and important area
> of research.

— Matthew J. Salganik, Professor of Sociology at Princeton University and author
of Bit by Bit: Social Research in the Digital Age

> “ This book could not be more welcome. Authored by two of the leading
> sociological researchers in the field of text analysis, it offers a
> comprehensive guide to state-of-the-art text analysis methods. But beyond just
> an introduction to methods, it provides a thoughtful and theoretically
> informed engagement about how we should think about, and interpret, the wealth
> of textual data that is now available. This is essential reading for anyone
> with an interest in computational social science.

— Carly Knight, Assistant Professor of Sociology at New York University

> “ This book is an excellent entry-point to modern ideas and tools for the
> quantitative analysis of textual data. Well-organized, approachable, and
> pragmatic, the book does a terrific job of showing why researchers find the
> ideas so interesting while also teaching the reader how to use the tools for
> themselves.

— Kieran Healy, Professor of Sociology at Duke University and author of Data
Visualization: A Practical Introduction

> “ Mapping Texts provides a timely and accessible foray into the evolving
> domain of computational text analysis, enriched with fascinating examples and
> cutting-edge techniques. The book is perfectly tailored for newcomers to
> text-based methods. Guiding readers through computational techniques without
> the complications of equations, the authors equip you with everything,
> including all the essential R code, to dive directly into text analysis.
> Moreover, the authors’ approach is grounded in a philosophy of language and
> text that harmonizes the positivist and interpretive traditions, making the
> book an excellent fit for an especially wide range of social science and
> humanities scholars and students.

— Anjali M. Bhatt, Assistant Professor of Business Administration at Harvard
Business School

> “ Stoltz and Taylor's book is easily one of the clearest and most
> comprehensive introductions to computational text analysis written to date.
> With impressive dexterity, they take readers through the principles and
> workflows that are necessary for studying texts with computational techniques,
> never forgetting that words are complex and multifaceted cultural objects. In
> its style, organization, and pedagogical approach, this book is nothing short
> of an exceptional achievement.

— Juan Pablo Pardo-Guerra, Associate Professor of Sociology the University of
California, San Diego, and co-editor of The Oxford Handbook of the Sociology of
Machine Learning



--------------------------------------------------------------------------------


SUPPORTING R PACKAGES