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Data Analytics in Digital Humanities

Author: Shalin Hai-Jew

Publisher: Springer

Published: 2017-05-03

Total Pages: 295

ISBN-13: 3319544993

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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.

Big Data in the Arts and Humanities

Author: Giovanni Schiuma

Publisher: CRC Press

Published: 2018-04-27

Total Pages: 399

ISBN-13: 1351172581

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As digital technologies occupy a more central role in working and everyday human life, individual and social realities are increasingly constructed and communicated through digital objects, which are progressively replacing and representing physical objects. They are even shaping new forms of virtual reality. This growing digital transformation coupled with technological evolution and the development of computer computation is shaping a cyber society whose working mechanisms are grounded upon the production, deployment, and exploitation of big data. In the arts and humanities, however, the notion of big data is still in its embryonic stage, and only in the last few years, have arts and cultural organizations and institutions, artists, and humanists started to investigate, explore, and experiment with the deployment and exploitation of big data as well as understand the possible forms of collaborations based on it. Big Data in the Arts and Humanities: Theory and Practice explores the meaning, properties, and applications of big data. This book examines therelevance of big data to the arts and humanities, digital humanities, and management of big data with and for the arts and humanities. It explores the reasons and opportunities for the arts and humanities to embrace the big data revolution. The book also delineates managerial implications to successfully shape a mutually beneficial partnership between the arts and humanities and the big data- and computational digital-based sciences. Big data and arts and humanities can be likened to the rational and emotional aspects of the human mind. This book attempts to integrate these two aspects of human thought to advance decision-making and to enhance the expression of the best of human life.

Book Synopsis Big Data in the Arts and Humanities by : Giovanni Schiuma

Download or read book Big Data in the Arts and Humanities written by Giovanni Schiuma and published by CRC Press. This book was released on 2018-04-27 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: As digital technologies occupy a more central role in working and everyday human life, individual and social realities are increasingly constructed and communicated through digital objects, which are progressively replacing and representing physical objects. They are even shaping new forms of virtual reality. This growing digital transformation coupled with technological evolution and the development of computer computation is shaping a cyber society whose working mechanisms are grounded upon the production, deployment, and exploitation of big data. In the arts and humanities, however, the notion of big data is still in its embryonic stage, and only in the last few years, have arts and cultural organizations and institutions, artists, and humanists started to investigate, explore, and experiment with the deployment and exploitation of big data as well as understand the possible forms of collaborations based on it. Big Data in the Arts and Humanities: Theory and Practice explores the meaning, properties, and applications of big data. This book examines therelevance of big data to the arts and humanities, digital humanities, and management of big data with and for the arts and humanities. It explores the reasons and opportunities for the arts and humanities to embrace the big data revolution. The book also delineates managerial implications to successfully shape a mutually beneficial partnership between the arts and humanities and the big data- and computational digital-based sciences. Big data and arts and humanities can be likened to the rational and emotional aspects of the human mind. This book attempts to integrate these two aspects of human thought to advance decision-making and to enhance the expression of the best of human life.

Big Data Analytics in Cognitive Social Media and Literary Texts

Author: Sanjiv Sharma

Publisher: Springer Nature

Published: 2021-10-10

Total Pages: 316

ISBN-13: 9811647291

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This book provides a comprehensive overview of the theory and praxis of Big Data Analytics and how these are used to extract cognition-related information from social media and literary texts. It presents analytics that transcends the borders of discipline-specific academic research and focuses on knowledge extraction, prediction, and decision-making in the context of individual, social, and national development. The content is divided into three main sections: the first of which discusses various approaches associated with Big Data Analytics, while the second addresses the security and privacy of big data in social media, and the last focuses on the literary text as the literary data in Big Data Analytics. Sharing valuable insights into the etiology behind human cognition and its reflection in social media and literary texts, the book benefits all those interested in analytics that can be applied to literature, history, philosophy, linguistics, literary theory, media & communication studies and computational/digital humanities.

Book Synopsis Big Data Analytics in Cognitive Social Media and Literary Texts by : Sanjiv Sharma

Download or read book Big Data Analytics in Cognitive Social Media and Literary Texts written by Sanjiv Sharma and published by Springer Nature. This book was released on 2021-10-10 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the theory and praxis of Big Data Analytics and how these are used to extract cognition-related information from social media and literary texts. It presents analytics that transcends the borders of discipline-specific academic research and focuses on knowledge extraction, prediction, and decision-making in the context of individual, social, and national development. The content is divided into three main sections: the first of which discusses various approaches associated with Big Data Analytics, while the second addresses the security and privacy of big data in social media, and the last focuses on the literary text as the literary data in Big Data Analytics. Sharing valuable insights into the etiology behind human cognition and its reflection in social media and literary texts, the book benefits all those interested in analytics that can be applied to literature, history, philosophy, linguistics, literary theory, media & communication studies and computational/digital humanities.

Research Methods for Creating and Curating Data in the Digital Humanities

Author: Matt Hayler

Publisher: Edinburgh University Press

Published: 2016-05-30

Total Pages: 256

ISBN-13: 1474409679

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As all scholars increasingly use digital tools to support their research, and every internet user becomes used to data being available, elucidating, and engaging, the creative aspects of Digital Humanities work are coming under increasing scrutiny. This volume explores the practice of making new tools, new images, new collections, and new artworks in an academic environment, detailing who needs to be involved and what their roles might be, and how they come together to produce knowledge as a collective. The chapters presented here demonstrate that creation is never neutral with political and theoretical concerns intentionally or unavoidably always being written into the fabric of what is being made, even if that's the seeming neatness of computer code. In presenting their own creative research, the writers in this volume offer examples of practice that will be of use to anyone interested in learning more about contemporary Digital Humanities scholarship and its implications.

Book Synopsis Research Methods for Creating and Curating Data in the Digital Humanities by : Matt Hayler

Download or read book Research Methods for Creating and Curating Data in the Digital Humanities written by Matt Hayler and published by Edinburgh University Press. This book was released on 2016-05-30 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: As all scholars increasingly use digital tools to support their research, and every internet user becomes used to data being available, elucidating, and engaging, the creative aspects of Digital Humanities work are coming under increasing scrutiny. This volume explores the practice of making new tools, new images, new collections, and new artworks in an academic environment, detailing who needs to be involved and what their roles might be, and how they come together to produce knowledge as a collective. The chapters presented here demonstrate that creation is never neutral with political and theoretical concerns intentionally or unavoidably always being written into the fabric of what is being made, even if that's the seeming neatness of computer code. In presenting their own creative research, the writers in this volume offer examples of practice that will be of use to anyone interested in learning more about contemporary Digital Humanities scholarship and its implications.

Research Methods for Reading Digital Data in the Digital Humanities

Author: Gabriele Griffin

Publisher: Edinburgh University Press

Published: 2016-02-15

Total Pages: 256

ISBN-13: 1474409628

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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

Book Synopsis Research Methods for Reading Digital Data in the Digital Humanities by : Gabriele Griffin

Download or read book Research Methods for Reading Digital Data in the Digital Humanities written by Gabriele Griffin and published by Edinburgh University Press. This book was released on 2016-02-15 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

The Shape of Data in Digital Humanities

Author: Julia Flanders

Publisher: Routledge

Published: 2018-11-02

Total Pages: 342

ISBN-13: 1317016157

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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 342 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.

Digital Humanities

Author: David M. Berry

Publisher: John Wiley & Sons

Published: 2017-05-30

Total Pages: 248

ISBN-13: 0745697690

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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.

Book Synopsis Digital Humanities by : David M. Berry

Download or read book Digital Humanities written by David M. Berry and published by John Wiley & Sons. This book was released on 2017-05-30 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Humanities Data Analysis

Author: Folgert Karsdorp

Publisher: Princeton University Press

Published: 2021-01-12

Total Pages: 352

ISBN-13: 0691172366

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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

The datafied society

Author: Mirko Tobias Schäfer

Publisher: Amsterdam University Press

Published: 2017-02-28

Total Pages:

ISBN-13: 9048531012

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As more and more aspects of everyday life are turned into machine-readable data, researchers are provided with rich resources for researching society. The novel methods and innovative tools to work with this data not only require new knowledge and skills, but also raise issues concerning the practices of investigation and publication. This book critically reflects on the role of data in academia and society and challenges overly optimistic expectations considering data practices as means for understanding social reality. It introduces its readers to the practices and methods for data analysis and visualization and raises questions not only about the politics of data tools, but also about the ethics in collecting, sifting through data, and presenting data research.

Book Synopsis The datafied society by : Mirko Tobias Schäfer

Download or read book The datafied society written by Mirko Tobias Schäfer and published by Amsterdam University Press. This book was released on 2017-02-28 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: As more and more aspects of everyday life are turned into machine-readable data, researchers are provided with rich resources for researching society. The novel methods and innovative tools to work with this data not only require new knowledge and skills, but also raise issues concerning the practices of investigation and publication. This book critically reflects on the role of data in academia and society and challenges overly optimistic expectations considering data practices as means for understanding social reality. It introduces its readers to the practices and methods for data analysis and visualization and raises questions not only about the politics of data tools, but also about the ethics in collecting, sifting through data, and presenting data research.

Humanities Data in R

Author: Taylor Arnold

Publisher: Springer

Published: 2015-09-23

Total Pages: 211

ISBN-13: 3319207024

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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.