Lauren Tilton – författare

Photographs are more than just illustrations of a moment in time, they offer a powerful way to interpret and understand the past like no other historical source can. U.S. History in 15 Photographs introduces this power through 15 iconic and lesser-known photographs representing key eras in American History. Taking the reader from Reconstruction and Westward Expansion, to the Roaring Twenties and the World Wars, right up to Modern American Culture, it offers a refreshing, visual account of American history.This volume reorients photography as a major source for understanding the past, expanding not only the stories that we tell, but the way we tell them. Teaching students how to understand, contextualize, and interpret historic photography, U.S. History in 15 Photographs centers diverse stories about the American experience by exploring topics around race, class, gender, disability, the environment, and social justice.The scholars who contributed to this volume show that photographs are more just illustrations from the past, but foundational sources with surprising revelations about the past.

Photographs are more than just illustrations of a moment in time, they offer a powerful way to interpret and understand the past like no other historical source can. U.S. History in 15 Photographs introduces this power through 15 iconic and lesser-known photographs representing key eras in American History. Taking the reader from Reconstruction and Westward Expansion, to the Roaring Twenties and the World Wars, right up to Modern American Culture, it offers a refreshing, visual account of American history.This volume reorients photography as a major source for understanding the past, expanding not only the stories that we tell, but the way we tell them. Teaching students how to understand, contextualize, and interpret historic photography, U.S. History in 15 Photographs centers diverse stories about the American experience by exploring topics around race, class, gender, disability, the environment, and social justice.The scholars who contributed to this volume show that photographs are more just illustrations from the past, but foundational sources with surprising revelations about the past.

The first book to intervene in debates on computation in the digital humanitiesBringing together leading experts from across North America and Europe, Computational Humanities redirects debates around computation and humanities digital scholarship from dualistic arguments to nuanced discourse centered around theories of knowledge and power. This volume is organized around four questions: Why or why not pursue computational humanities? How do we engage in computational humanities? What can we study using these methods? Who are the stakeholders?   Recent advances in technologies for image and sound processing have expanded computational approaches to cultural forms beyond text, and new forms of data, from listservs and code repositories to tweets and other social media content, have enlivened debates about what counts as digital humanities scholarship. Providing case studies of collaborations between humanities-centered and computation-centered researchers, this volume highlights both opportunities and frictions, showing that data and computation are as much about power, prestige, and precarity as they are about p-values.   Contributors: Mark Algee-Hewitt, Stanford U; David Bamman, U of California, Berkeley; Kaspar Beelen, U of London; Peter Bell, Philipps U of Marburg; Tobias Blanke, U of Amsterdam; Julia Damerow, Arizona State U; Quinn Dombrowski, Stanford U; Crystal Nicole Eddins, U of Pittsburgh; Abraham Gibson, U of Texas at San Antonio; Tassie Gniady; Crystal Hall, Bowdoin College; Vanessa M. Holden, U of Kentucky; David Kloster, Indiana U; Manfred D. Laubichler, Arizona State U; Katherine McDonough, Lancaster U; Barbara McGillivray, King’s College London; Megan Meredith-Lobay, Simon Fraser U; Federico Nanni, Alan Turing Institute; Fabian Offert, U of California, Santa Barbara; Hannah Ringler, Illinois Institute of Technology; Roopika Risam, Dartmouth College; Joshua D. Rothman, U of Alabama; Benjamin M. Schmidt; Lisa Tagliaferri, Rutgers U; Jeffrey Tharsen, U of Chicago; Marieke van Erp, Royal Netherlands Academy of Arts and Sciences; Lee Zickel, Case Western Reserve U.

The first book to intervene in debates on computation in the digital humanitiesBringing together leading experts from across North America and Europe, Computational Humanities redirects debates around computation and humanities digital scholarship from dualistic arguments to nuanced discourse centered around theories of knowledge and power. This volume is organized around four questions: Why or why not pursue computational humanities? How do we engage in computational humanities? What can we study using these methods? Who are the stakeholders?   Recent advances in technologies for image and sound processing have expanded computational approaches to cultural forms beyond text, and new forms of data, from listservs and code repositories to tweets and other social media content, have enlivened debates about what counts as digital humanities scholarship. Providing case studies of collaborations between humanities-centered and computation-centered researchers, this volume highlights both opportunities and frictions, showing that data and computation are as much about power, prestige, and precarity as they are about p-values.   Contributors: Mark Algee-Hewitt, Stanford U; David Bamman, U of California, Berkeley; Kaspar Beelen, U of London; Peter Bell, Philipps U of Marburg; Tobias Blanke, U of Amsterdam; Julia Damerow, Arizona State U; Quinn Dombrowski, Stanford U; Crystal Nicole Eddins, U of Pittsburgh; Abraham Gibson, U of Texas at San Antonio; Tassie Gniady; Crystal Hall, Bowdoin College; Vanessa M. Holden, U of Kentucky; David Kloster, Indiana U; Manfred D. Laubichler, Arizona State U; Katherine McDonough, Lancaster U; Barbara McGillivray, King’s College London; Megan Meredith-Lobay, Simon Fraser U; Federico Nanni, Alan Turing Institute; Fabian Offert, U of California, Santa Barbara; Hannah Ringler, Illinois Institute of Technology; Roopika Risam, Dartmouth College; Joshua D. Rothman, U of Alabama; Benjamin M. Schmidt; Lisa Tagliaferri, Rutgers U; Jeffrey Tharsen, U of Chicago; Marieke van Erp, Royal Netherlands Academy of Arts and Sciences; Lee Zickel, Case Western Reserve U.

This book teaches readers to integrate data analysis techniques into humanities research practices using the R programming language. Methods for general-purpose visualization and analysis are introduced first, followed by domain-specific techniques for working with networks, text, geospatial data, temporal data, and images.

This book teaches readers to integrate data analysis techniques into humanities research practices using the R programming language. Methods for general-purpose visualization and analysis are introduced first, followed by domain-specific techniques for working with networks, text, geospatial data, temporal data, and images. The book is designed to be a bridge between quantitative and qualitative methods, individual and collaborative work, and the humanities and social sciences. The second edition of the text is a significant revision, with almost every aspect of the text rewritten in some way. The most notable difference is the incorporation of new R packages such as ggplot2 and dplyr that center broad data-science concepts.This 2nd edition of Humanities Data with R does not presuppose background programming experience. Early chapters take readers from R set-up to exploratory data analysis, with one chapter dedicated to each stage of the data-science pipeline (data collection, visualization, manipulation, and relational joins). Following this, text analysis, networks, temporal data, geospatial data, and image analysis each have a dedicated chapter. These are grounded in examples to move readers beyond the intimidation of adding new tools to their research. The final section of the book extends the core material with additional computer science techniques for processing large datasets.Everything is hands-on: image analysis is explained using digitized photographs from the 1930s, and networks are applied to page links on Wikipedia. After working through these examples with the provided data, code and book website, readers are prepared to apply new methods to their own work. The open source R programming language, with its myriad packages and popularity within the sciences and social sciences, is particularly well-suited to working with humanities data. R packages are also highlighted in an appendix.The methodology will have wide application in classrooms and self-study for the humanities, but also for use in linguistics, anthropology, and political science. Outside the classroom, this intersection of humanities and computing is particularly relevant for research and new modes of dissemination across archives, museums and libraries.