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Author: Shalin Hai-Jew
Publisher: Springer
ISBN: 3319544993
Category : Computers
Languages : en
Pages : 304
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Book Description
This book covers computationally innovative methods and technologies including data collection and elicitation, data processing, data analysis, data visualizations, and data presentation. It explores how digital humanists have harnessed the hypersociality and social technologies, benefited from the open-source sharing not only of data but of code, and made technological capabilities a critical part of humanities work. Chapters are written by researchers from around the world, bringing perspectives from diverse fields and subject areas. The respective authors describe their work, their research, and their learning. Topics include semantic web for cultural heritage valorization, machine learning for parody detection by classification, psychological text analysis, crowdsourcing imagery coding in natural disasters, and creating inheritable digital codebooks.Designed for researchers and academics, this book is suitable for those interested in methodologies and analytics that can be applied in literature, history, philosophy, linguistics, and related disciplines. Professionals such as librarians, archivists, and historians will also find the content informative and instructive.
Author: Shalin Hai-Jew
Publisher: Springer
ISBN: 3319544993
Category : Computers
Languages : en
Pages : 304
Get Book Here
Book Description
This book covers computationally innovative methods and technologies including data collection and elicitation, data processing, data analysis, data visualizations, and data presentation. It explores how digital humanists have harnessed the hypersociality and social technologies, benefited from the open-source sharing not only of data but of code, and made technological capabilities a critical part of humanities work. Chapters are written by researchers from around the world, bringing perspectives from diverse fields and subject areas. The respective authors describe their work, their research, and their learning. Topics include semantic web for cultural heritage valorization, machine learning for parody detection by classification, psychological text analysis, crowdsourcing imagery coding in natural disasters, and creating inheritable digital codebooks.Designed for researchers and academics, this book is suitable for those interested in methodologies and analytics that can be applied in literature, history, philosophy, linguistics, and related disciplines. Professionals such as librarians, archivists, and historians will also find the content informative and instructive.
Author: Folgert Karsdorp
Publisher: Princeton University Press
ISBN: 0691172366
Category : Computers
Languages : en
Pages : 352
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Book Description
A practical guide to data-intensive humanities research using the Python programming language The use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers to discover patterns in a vast range of source materials. Despite this growth, there are few resources addressed to students and scholars who wish to take advantage of these powerful tools. Humanities Data Analysis offers the first intermediate-level guide to quantitative data analysis for humanities students and scholars using the Python programming language. This practical textbook, which assumes a basic knowledge of Python, teaches readers the necessary skills for conducting humanities research in the rapidly developing digital environment. The book begins with an overview of the place of data science in the humanities, and proceeds to cover data carpentry: the essential techniques for gathering, cleaning, representing, and transforming textual and tabular data. Then, drawing from real-world, publicly available data sets that cover a variety of scholarly domains, the book delves into detailed case studies. Focusing on textual data analysis, the authors explore such diverse topics as network analysis, genre theory, onomastics, literacy, author attribution, mapping, stylometry, topic modeling, and time series analysis. Exercises and resources for further reading are provided at the end of each chapter. An ideal resource for humanities students and scholars aiming to take their Python skills to the next level, Humanities Data Analysis illustrates the benefits that quantitative methods can bring to complex research questions. Appropriate for advanced undergraduates, graduate students, and scholars with a basic knowledge of Python Applicable to many humanities disciplines, including history, literature, and sociology Offers real-world case studies using publicly available data sets Provides exercises at the end of each chapter for students to test acquired skills Emphasizes visual storytelling via data visualizations
Author: Gabriele Griffin
Publisher: Edinburgh University Press
ISBN: 1474409628
Category : Reference
Languages : en
Pages : 223
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Book Description
The first volume to introduce the techniques and methods of reading digital material for researchDigital Humanities has become one of the new domains of academe at the interface of technological development, epistemological change, and methodological concerns. This volume explores how digital material might be read or utilized in research, whether that material is digitally born as fanfiction, for example, mostly is, or transposed from other sources. The volume asks questions such as what happens when text is transformed from printed into digital matter, and how that impacts on the methods we bring to bear on exploring that technologized matter, for example in the case of digital editions. Issues such as how to analyse visual material in digital archives or Twitter feeds, how to engage in data mining, what it means to undertake crowd-sourcing, big data, and what digital network analyses can tell us about online interactions are dealt with. This will give Humanities researchers ideas for doing digitally based research and also suggest ways of engaging with new digital research methods. Key featuresFirst volume centred on the navigation and interpretation of digital material as research methods in the HumanitiesUp-to-date analyses of issues and methods including big data, crowdsourcing, digital network analysis, working with digital additionsBased on actual research projects such as para-textual work with fanfiction, reading twitter, different kinds of distant and close readings
Author: Ted Underwood
Publisher: Stanford University Press
ISBN: 0804788448
Category : Literary Criticism
Languages : en
Pages : 210
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Book Description
In the mid-nineteenth century, the study of English literature began to be divided into courses that surveyed discrete "periods." Since that time, scholars' definitions of literature and their rationales for teaching it have changed radically. But the periodized structure of the curriculum has remained oddly unshaken, as if the exercise of contrasting one literary period with another has an importance that transcends the content of any individual course. Why Literary Periods Mattered explains how historical contrast became central to literary study, and why it remained institutionally central in spite of critical controversy about literature itself. Organizing literary history around contrast rather than causal continuity helped literature departments separate themselves from departments of history. But critics' long reliance on a rhetoric of contrasted movements and fateful turns has produced important blind spots in the discipline. In the twenty-first century, Underwood argues, literary study may need digital technology in particular to develop new methods of reasoning about gradual, continuous change.
Author: Matthew K. Gold
Publisher: U of Minnesota Press
ISBN: 1452961670
Category : Social Science
Languages : en
Pages : 693
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Book Description
The latest installment of a digital humanities bellwether Contending with recent developments like the shocking 2016 U.S. Presidential election, the radical transformation of the social web, and passionate debates about the future of data in higher education, Debates in the Digital Humanities 2019 brings together a broad array of important, thought-provoking perspectives on the field’s many sides. With a wide range of subjects including gender-based assumptions made by algorithms, the place of the digital humanities within art history, data-based methods for exhuming forgotten histories, video games, three-dimensional printing, and decolonial work, this book assembles a who’s who of the field in more than thirty impactful essays. Contributors: Rafael Alvarado, U of Virginia; Taylor Arnold, U of Richmond; James Baker, U of Sussex; Kathi Inman Berens, Portland State U; David M. Berry, U of Sussex; Claire Bishop, The Graduate Center, CUNY; James Coltrain, U of Nebraska–Lincoln; Crunk Feminist Collective; Johanna Drucker, U of California–Los Angeles; Jennifer Edmond, Trinity College; Marta Effinger-Crichlow, New York City College of Technology–CUNY; M. Beatrice Fazi, U of Sussex; Kevin L. Ferguson, Queens College–CUNY; Curtis Fletcher, U of Southern California; Neil Fraistat, U of Maryland; Radhika Gajjala, Bowling Green State U; Michael Gavin, U of South Carolina; Andrew Goldstone, Rutgers U; Andrew Gomez, U of Puget Sound; Elyse Graham, Stony Brook U; Brian Greenspan, Carleton U; John Hunter, Bucknell U; Steven J. Jackson, Cornell U; Collin Jennings, Miami U; Lauren Kersey, Saint Louis U; Kari Kraus, U of Maryland; Seth Long, U of Nebraska, Kearney; Laura Mandell, Texas A&M U; Rachel Mann, U of South Carolina; Jason Mittell, Middlebury College; Lincoln A. Mullen, George Mason U; Trevor Muñoz, U of Maryland; Safiya Umoja Noble, U of Southern California; Jack Norton, Normandale Community College; Bethany Nowviskie, U of Virginia; Élika Ortega, Northeastern U; Marisa Parham, Amherst College; Jussi Parikka, U of Southampton; Kyle Parry, U of California, Santa Cruz; Brad Pasanek, U of Virginia; Stephen Ramsay, U of Nebraska–Lincoln; Matt Ratto, U of Toronto; Katie Rawson, U of Pennsylvania; Ben Roberts, U of Sussex; David S. Roh, U of Utah; Mark Sample, Davidson College; Moacir P. de Sá Pereira, New York U; Tim Sherratt, U of Canberra; Bobby L. Smiley, Vanderbilt U; Lauren Tilton, U of Richmond; Ted Underwood, U of Illinois, Urbana-Champaign; Megan Ward, Oregon State U; Claire Warwick, Durham U; Alban Webb, U of Sussex; Adrian S. Wisnicki, U of Nebraska–Lincoln.
Author: Matthew K. Gold
Publisher: U of Minnesota Press
ISBN: 1452951497
Category : Education
Languages : en
Pages : 812
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Book Description
Pairing full-length scholarly essays with shorter pieces drawn from scholarly blogs and conference presentations, as well as commissioned interviews and position statements, Debates in the Digital Humanities 2016 reveals a dynamic view of a field in negotiation with its identity, methods, and reach. Pieces in the book explore how DH can and must change in response to social justice movements and events like #Ferguson; how DH alters and is altered by community college classrooms; and how scholars applying DH approaches to feminist studies, queer studies, and black studies might reframe the commitments of DH analysts. Numerous contributors examine the movement of interdisciplinary DH work into areas such as history, art history, and archaeology, and a special forum on large-scale text mining brings together position statements on a fast-growing area of DH research. In the multivalent aspects of its arguments, progressing across a range of platforms and environments, Debates in the Digital Humanities 2016 offers a vision of DH as an expanded field—new possibilities, differently structured. Published simultaneously in print, e-book, and interactive webtext formats, each DH annual will be a book-length publication highlighting the particular debates that have shaped the discipline in a given year. By identifying key issues as they unfold, and by providing a hybrid model of open-access publication, these volumes and the Debates in the Digital Humanities series will articulate the present contours of the field and help forge its future. Contributors: Moya Bailey, Northeastern U; Fiona Barnett; Matthew Battles, Harvard U; Jeffrey M. Binder; Zach Blas, U of London; Cameron Blevins, Rutgers U; Sheila A. Brennan, George Mason U; Timothy Burke, Swarthmore College; Rachel Sagner Buurma, Swarthmore College; Micha Cárdenas, U of Washington–Bothell; Wendy Hui Kyong Chun, Brown U; Tanya E. Clement, U of Texas–Austin; Anne Cong-Huyen, Whittier College; Ryan Cordell, Northeastern U; Tressie McMillan Cottom, Virginia Commonwealth U; Amy E. Earhart, Texas A&M U; Domenico Fiormonte, U of Roma Tre; Paul Fyfe, North Carolina State U; Jacob Gaboury, Stony Brook U; Kim Gallon, Purdue U; Alex Gil, Columbia U; Brian Greenspan, Carleton U; Richard Grusin, U of Wisconsin, Milwaukee; Michael Hancher, U of Minnesota; Molly O’Hagan Hardy; David L. Hoover, New York U; Wendy F. Hsu; Patrick Jagoda, U of Chicago; Jessica Marie Johnson, Michigan State U; Steven E. Jones, Loyola U; Margaret Linley, Simon Fraser U; Alan Liu, U of California, Santa Barbara; Elizabeth Losh, U of California, San Diego; Alexis Lothian, U of Maryland; Michael Maizels, Wellesley College; Mark C. Marino, U of Southern California; Anne B. McGrail, Lane Community College; Bethany Nowviskie, U of Virginia; Julianne Nyhan, U College London; Amanda Phillips, U of California, Davis; Miriam Posner, U of California, Los Angeles; Rita Raley, U of California, Santa Barbara; Stephen Ramsay, U of Nebraska–Lincoln; Margaret Rhee, U of Oregon; Lisa Marie Rhody, Graduate Center, CUNY; Roopika Risam, Salem State U; Stephen Robertson, George Mason U; Mark Sample, Davidson College; Jentery Sayers, U of Victoria; Benjamin M. Schmidt, Northeastern U; Scott Selisker, U of Arizona; Jonathan Senchyne, U of Wisconsin, Madison; Andrew Stauffer, U of Virginia; Joanna Swafford, SUNY New Paltz; Toniesha L. Taylor, Prairie View A&M U; Dennis Tenen; Melissa Terras, U College London; Anna Tione; Ted Underwood, U of Illinois, Urbana–Champaign; Ethan Watrall, Michigan State U; Jacqueline Wernimont, Arizona State U; Laura Wexler, Yale U; Hong-An Wu, U of Illinois, Urbana–Champaign.
Author: Shu-Heng Chen
Publisher: Springer
ISBN: 3319954652
Category : Computers
Languages : en
Pages : 391
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Book Description
This edited volume focuses on big data implications for computational social science and humanities from management to usage. The first part of the book covers geographic data, text corpus data, and social media data, and exemplifies their concrete applications in a wide range of fields including anthropology, economics, finance, geography, history, linguistics, political science, psychology, public health, and mass communications. The second part of the book provides a panoramic view of the development of big data in the fields of computational social sciences and humanities. The following questions are addressed: why is there a need for novel data governance for this new type of data?, why is big data important for social scientists?, and how will it revolutionize the way social scientists conduct research? With the advent of the information age and technologies such as Web 2.0, ubiquitous computing, wearable devices, and the Internet of Things, digital society has fundamentally changed what we now know as "data", the very use of this data, and what we now call "knowledge". Big data has become the standard in social sciences, and has made these sciences more computational. Big Data in Computational Social Science and Humanities will appeal to graduate students and researchers working in the many subfields of the social sciences and humanities.
Author: Anne Burdick
Publisher: MIT Press
ISBN: 026252886X
Category : Social Science
Languages : en
Pages : 153
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Book Description
A visionary report on the revitalization of the liberal arts tradition in the electronically inflected, design-driven, multimedia language of the twenty-first century. Digital_Humanities is a compact, game-changing report on the state of contemporary knowledge production. Answering the question “What is digital humanities?,” it provides an in-depth examination of an emerging field. This collaboratively authored and visually compelling volume explores methodologies and techniques unfamiliar to traditional modes of humanistic inquiry—including geospatial analysis, data mining, corpus linguistics, visualization, and simulation—to show their relevance for contemporary culture. Written by five leading practitioner-theorists whose varied backgrounds embody the intellectual and creative diversity of the field, Digital_Humanities is a vision statement for the future, an invitation to engage, and a critical tool for understanding the shape of new scholarship.
Author: David M. Berry
Publisher: John Wiley & Sons
ISBN: 0745697690
Category : Social Science
Languages : en
Pages : 176
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Book Description
As the twenty-first century unfolds, computers challenge the way in which we think about culture, society and what it is to be human: areas traditionally explored by the humanities. In a world of automation, Big Data, algorithms, Google searches, digital archives, real-time streams and social networks, our use of culture has been changing dramatically. The digital humanities give us powerful theories, methods and tools for exploring new ways of being in a digital age. Berry and Fagerjord provide a compelling guide, exploring the history, intellectual work, key arguments and ideas of this emerging discipline. They also offer an important critique, suggesting ways in which the humanities can be enriched through computing, but also how cultural critique can transform the digital humanities. Digital Humanities will be an essential book for students and researchers in this new field but also related areas, such as media and communications, digital media, sociology, informatics, and the humanities more broadly.
Author: Annika Richterich
Publisher: University of Westminster Press
ISBN: 1911534734
Category : Social Science
Languages : en
Pages : 156
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Book Description
This book highlights that the capacity for gathering, analysing, and utilising vast amounts of digital (user) data raises significant ethical issues. Annika Richterich provides a systematic contemporary overview of the field of critical data studies that reflects on practices of digital data collection and analysis. The book assesses in detail one big data research area: biomedical studies, focused on epidemiological surveillance. Specific case studies explore how big data have been used in academic work. The Big Data Agenda concludes that the use of big data in research urgently needs to be considered from the vantage point of ethics and social justice. Drawing upon discourse ethics and critical data studies, Richterich argues that entanglements between big data research and technology/ internet corporations have emerged. In consequence, more opportunities for discussing and negotiating emerging research practices and their implications for societal values are needed.
