Humanities Data Analysis eBook Download PDF

Download Humanities Data Analysis full books in PDF, epub, and Kindle. Read online Humanities Data Analysis ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Humanities Data Analysis

Author: Folgert Karsdorp

Publisher: Princeton University Press

Published: 2021-01-12

Total Pages: 352

ISBN-13: 0691172366

DOWNLOAD EBOOK

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

Book Synopsis Humanities Data Analysis by : Folgert Karsdorp

Download or read book Humanities Data Analysis written by Folgert Karsdorp and published by Princeton University Press. This book was released on 2021-01-12 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Data Analytics in Digital Humanities

Author: Shalin Hai-Jew

Publisher: Springer

Published: 2017-05-03

Total Pages: 295

ISBN-13: 3319544993

DOWNLOAD EBOOK

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.

Book Synopsis Data Analytics in Digital Humanities by : Shalin Hai-Jew

Download or read book Data Analytics in Digital Humanities written by Shalin Hai-Jew and published by Springer. This book was released on 2017-05-03 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Humanities Data Analysis

Author: Folgert Karsdorp

Publisher: Princeton University Press

Published: 2021-01-12

Total Pages: 352

ISBN-13: 0691172366

DOWNLOAD EBOOK

Book Synopsis Humanities Data Analysis by : Folgert Karsdorp

Humanities Data in R

Author: Taylor Arnold

Publisher: Springer

Published: 2015-09-23

Total Pages: 211

ISBN-13: 3319207024

DOWNLOAD EBOOK

This pioneering book teaches readers to use R within four core analytical areas applicable to the Humanities: networks, text, geospatial data, and images. This book is also designed to be a bridge: between quantitative and qualitative methods, individual and collaborative work, and the humanities and social sciences. Humanities Data with R does not presuppose background programming experience. Early chapters take readers from R set-up to exploratory data analysis (continuous and categorical data, multivariate analysis, and advanced graphics with emphasis on aesthetics and facility). Following this, networks, geospatial data, image data, natural language processing and text analysis each have a dedicated chapter. Each chapter is grounded in examples to move readers beyond the intimidation of adding new tools to their research. Everything is hands-on: networks are explained using U.S. Supreme Court opinions, and low-level NLP methods are applied to short stories by Sir Arthur Conan Doyle. 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. This book uses an expanded conception of the forms data may take and the information it represents. 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.

Book Synopsis Humanities Data in R by : Taylor Arnold

Download or read book Humanities Data in R written by Taylor Arnold and published by Springer. This book was released on 2015-09-23 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: This pioneering book teaches readers to use R within four core analytical areas applicable to the Humanities: networks, text, geospatial data, and images. This book is also designed to be a bridge: between quantitative and qualitative methods, individual and collaborative work, and the humanities and social sciences. Humanities Data with R does not presuppose background programming experience. Early chapters take readers from R set-up to exploratory data analysis (continuous and categorical data, multivariate analysis, and advanced graphics with emphasis on aesthetics and facility). Following this, networks, geospatial data, image data, natural language processing and text analysis each have a dedicated chapter. Each chapter is grounded in examples to move readers beyond the intimidation of adding new tools to their research. Everything is hands-on: networks are explained using U.S. Supreme Court opinions, and low-level NLP methods are applied to short stories by Sir Arthur Conan Doyle. 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. This book uses an expanded conception of the forms data may take and the information it represents. 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.

Debates in the Digital Humanities 2016

Author: Matthew K. Gold

Publisher: U of Minnesota Press

Published: 2016-05-18

Total Pages: 838

ISBN-13: 1452951497

DOWNLOAD EBOOK

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.

Book Synopsis Debates in the Digital Humanities 2016 by : Matthew K. Gold

Download or read book Debates in the Digital Humanities 2016 written by Matthew K. Gold and published by U of Minnesota Press. This book was released on 2016-05-18 with total page 838 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Quantitative Methods in the Humanities

Author: Claire Lemercier

Publisher:

Published: 2019

Total Pages: 188

ISBN-13: 9780813942698

DOWNLOAD EBOOK

This timely and lucid guide is intended for students and scholars working on all historical periods and topics in the humanities and social sciences--especially for those who do not think of themselves as experts in quantification, "big data," or "digital humanities." The authors reveal quantification to be a powerful and versatile tool, applicable to a myriad of materials from the past. Their book, accessible to complete beginners, offers detailed advice and practical tips on how to build a dataset from historical sources and how to categorize it according to specific research questions. Drawing on examples from works in social, political, economic, and cultural history, the book guides readers through a wide range of methods, including sampling, cross-tabulations, statistical tests, regression, factor analysis, network analysis, sequence analysis, event history analysis, geographical information systems, text analysis, and visualization. The requirements, advantages, and pitfalls of these techniques are presented in layperson's terms, avoiding mathematical terminology. Conceived primarily for historians, the book will prove invaluable to other humanists, as well as to social scientists looking for a nontechnical introduction to quantitative methods. Covering the most recent techniques, in addition to others not often enough discussed, the book will also have much to offer to the most seasoned practitioners of quantification.

Book Synopsis Quantitative Methods in the Humanities by : Claire Lemercier

Download or read book Quantitative Methods in the Humanities written by Claire Lemercier and published by . This book was released on 2019 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: This timely and lucid guide is intended for students and scholars working on all historical periods and topics in the humanities and social sciences--especially for those who do not think of themselves as experts in quantification, "big data," or "digital humanities." The authors reveal quantification to be a powerful and versatile tool, applicable to a myriad of materials from the past. Their book, accessible to complete beginners, offers detailed advice and practical tips on how to build a dataset from historical sources and how to categorize it according to specific research questions. Drawing on examples from works in social, political, economic, and cultural history, the book guides readers through a wide range of methods, including sampling, cross-tabulations, statistical tests, regression, factor analysis, network analysis, sequence analysis, event history analysis, geographical information systems, text analysis, and visualization. The requirements, advantages, and pitfalls of these techniques are presented in layperson's terms, avoiding mathematical terminology. Conceived primarily for historians, the book will prove invaluable to other humanists, as well as to social scientists looking for a nontechnical introduction to quantitative methods. Covering the most recent techniques, in addition to others not often enough discussed, the book will also have much to offer to the most seasoned practitioners of quantification.

The Shape of Data in Digital Humanities

Author: Julia Flanders

Publisher: Routledge

Published: 2018-11-02

Total Pages: 382

ISBN-13: 1317016149

DOWNLOAD EBOOK

Data and its technologies now play a large and growing role in humanities research and teaching. This book addresses the needs of humanities scholars who seek deeper expertise in the area of data modeling and representation. The authors, all experts in digital humanities, offer a clear explanation of key technical principles, a grounded discussion of case studies, and an exploration of important theoretical concerns. The book opens with an orientation, giving the reader a history of data modeling in the humanities and a grounding in the technical concepts necessary to understand and engage with the second part of the book. The second part of the book is a wide-ranging exploration of topics central for a deeper understanding of data modeling in digital humanities. Chapters cover data modeling standards and the role they play in shaping digital humanities practice, traditional forms of modeling in the humanities and how they have been transformed by digital approaches, ontologies which seek to anchor meaning in digital humanities resources, and how data models inhabit the other analytical tools used in digital humanities research. It concludes with a glossary chapter that explains specific terms and concepts for data modeling in the digital humanities context. This book is a unique and invaluable resource for teaching and practising data modeling in a digital humanities context.

Book Synopsis The Shape of Data in Digital Humanities by : Julia Flanders

Download or read book The Shape of Data in Digital Humanities written by Julia Flanders and published by Routledge. This book was released on 2018-11-02 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data and its technologies now play a large and growing role in humanities research and teaching. This book addresses the needs of humanities scholars who seek deeper expertise in the area of data modeling and representation. The authors, all experts in digital humanities, offer a clear explanation of key technical principles, a grounded discussion of case studies, and an exploration of important theoretical concerns. The book opens with an orientation, giving the reader a history of data modeling in the humanities and a grounding in the technical concepts necessary to understand and engage with the second part of the book. The second part of the book is a wide-ranging exploration of topics central for a deeper understanding of data modeling in digital humanities. Chapters cover data modeling standards and the role they play in shaping digital humanities practice, traditional forms of modeling in the humanities and how they have been transformed by digital approaches, ontologies which seek to anchor meaning in digital humanities resources, and how data models inhabit the other analytical tools used in digital humanities research. It concludes with a glossary chapter that explains specific terms and concepts for data modeling in the digital humanities context. This book is a unique and invaluable resource for teaching and practising data modeling in a digital humanities context.

Data Analysis for Social Science

Author: Elena Llaudet

Publisher: Princeton University Press

Published: 2022-11-29

Total Pages: 256

ISBN-13: 0691199434

DOWNLOAD EBOOK

"Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--

Book Synopsis Data Analysis for Social Science by : Elena Llaudet

Download or read book Data Analysis for Social Science written by Elena Llaudet and published by Princeton University Press. This book was released on 2022-11-29 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--

Visualization and Interpretation

Author: Johanna Drucker

Publisher: MIT Press

Published: 2020-11-10

Total Pages: 205

ISBN-13: 0262044730

DOWNLOAD EBOOK

An analysis of visual epistemology in the digital humanities, with attention to the need for interpretive digital tools within humanities contexts. In the several decades since humanists have taken up computational tools, they have borrowed many techniques from other fields, including visualization methods to create charts, graphs, diagrams, maps, and other graphic displays of information. But are these visualizations actually adequate for the interpretive approach that distinguishes much of the work in the humanities? Information visualization, as practiced today, lacks the interpretive frameworks required for humanities-oriented methodologies. In this book, Johanna Drucker continues her interrogation of visual epistemology in the digital humanities, reorienting the creation of digital tools within humanities contexts. Drucker examines various theoretical understandings of visual images and their relation to knowledge and how the specifics of the graphical are to be engaged directly as a primary means of knowledge production for digital humanities. She draws on work from aesthetics, critical theory, and formal study of graphical systems, addressing them within the specific framework of computational and digital activity as they apply to digital humanities. Finally, she presents a series of standard problems in visualization for the humanities (including time/temporality, space/spatial relations, and data analysis), posing the investigation in terms of innovative graphical systems informed by probabilistic critical hermeneutics. She concludes with a final brief sketch of discovery tools as an additional interface into which modeling can be worked.

Book Synopsis Visualization and Interpretation by : Johanna Drucker

Download or read book Visualization and Interpretation written by Johanna Drucker and published by MIT Press. This book was released on 2020-11-10 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: An analysis of visual epistemology in the digital humanities, with attention to the need for interpretive digital tools within humanities contexts. In the several decades since humanists have taken up computational tools, they have borrowed many techniques from other fields, including visualization methods to create charts, graphs, diagrams, maps, and other graphic displays of information. But are these visualizations actually adequate for the interpretive approach that distinguishes much of the work in the humanities? Information visualization, as practiced today, lacks the interpretive frameworks required for humanities-oriented methodologies. In this book, Johanna Drucker continues her interrogation of visual epistemology in the digital humanities, reorienting the creation of digital tools within humanities contexts. Drucker examines various theoretical understandings of visual images and their relation to knowledge and how the specifics of the graphical are to be engaged directly as a primary means of knowledge production for digital humanities. She draws on work from aesthetics, critical theory, and formal study of graphical systems, addressing them within the specific framework of computational and digital activity as they apply to digital humanities. Finally, she presents a series of standard problems in visualization for the humanities (including time/temporality, space/spatial relations, and data analysis), posing the investigation in terms of innovative graphical systems informed by probabilistic critical hermeneutics. She concludes with a final brief sketch of discovery tools as an additional interface into which modeling can be worked.

Computational History and Data-Driven Humanities

Author: Bojan Bozic

Publisher: Springer

Published: 2016-11-07

Total Pages: 133

ISBN-13: 3319462245

DOWNLOAD EBOOK

This book constitutes the refereed post-proceedings of the Second IFIP WG 12.7 International Workshop on Computational History and Data-Driven Humanities, held in Dublin, Ireland, in May 2016. The 7 full papers presented together with 2 invited talks and 4 lightning talks were carefully reviewed and selected from 14 submissions. The papers focus on the challenge and opportunities of data-driven humanities and cover topics at the interface between computer science, social science, humanities, and mathematics.

Book Synopsis Computational History and Data-Driven Humanities by : Bojan Bozic

Download or read book Computational History and Data-Driven Humanities written by Bojan Bozic and published by Springer. This book was released on 2016-11-07 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-proceedings of the Second IFIP WG 12.7 International Workshop on Computational History and Data-Driven Humanities, held in Dublin, Ireland, in May 2016. The 7 full papers presented together with 2 invited talks and 4 lightning talks were carefully reviewed and selected from 14 submissions. The papers focus on the challenge and opportunities of data-driven humanities and cover topics at the interface between computer science, social science, humanities, and mathematics.