A Data-Driven Analysis of Cemeteries and Social Reform in Paris, 1804-1924
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This book takes a novel, data-driven approach to the cemeteries of Paris, analyzing a largely text-based body of archival material as proxy evidence for visual material that has been lost due to systematic, and legally sanctioned, acts of erasure. This study represents the first full-length study of vernacular monuments in France and the entrepreneurs who made them. It also provides methodical considerations, at the intersection of the computational and digital humanities for managing survival biases in extant historical evidence, that are applicable beyond the thematic focus of this book. Since extant examples of these more inconspicuous monuments are rare, this project employs both distant and close viewing--analyzing commercial almanacs, work logs, and burial records in aggregates alongside detailed case studies--to compensate for gaps in the material record. The book will be of interest to scholars working in visual culture, popular culture, digital humanities, and French history.
Connecting Communities in Archaic Greece
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This is a new history of Greece in the seventh and sixth centuries BC written for the twenty-first century. It brings together archaeological data from over 100 years of 'Big Dig' excavation in Greece, employing experimental data analysis techniques from the digital humanities to identify new patterns about Archaic Greece. By modelling trade routes, political alliances, and the formation of personal- and state-networks, the book sheds new light on how exactly the early communities of the Aegean basin were plugged into one another. Returning to the long-debated question of 'what is a polis?', this study also challenges Classical Archaeology more generally: that the discipline has at its fingertips significant datasets that can contribute to substantive historical debate -and that what can be done for the next generation of scholarship is to re-engage with old material in a new way.
The Shape of Data in Digital Humanities
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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.
Data Analytics in Digital Humanities
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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.
Research Methods for Reading Digital Data in the Digital Humanities
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Digital 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.
Humanities Data in R
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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.
Exploring Big Historical Data
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The Digital Humanities have arrived at a moment when digital Big Data is becoming more readily available, opening exciting new avenues of inquiry but also new challenges. This pioneering book describes and demonstrates the ways these data can be explored to construct cultural heritage knowledge, for research and in teaching and learning. It helps humanities scholars to grasp Big Data in order to do their work, whether that means understanding the underlying algorithms at work in search engines, or designing and using their own tools to process large amounts of information.Demonstrating what digital tools have to offer and also what 'digital' does to how we understand the past, the authors introduce the many different tools and developing approaches in Big Data for historical and humanistic scholarship, show how to use them, what to be wary of, and discuss the kinds of questions and new perspectives this new macroscopic perspective opens up. Authored 'live' online with ongoing feedback from the wider digital history community, Exploring Big Historical Data breaks new ground and sets the direction for the conversation into the future. It represents the current state-of-the-art thinking in the field and exemplifies the way that digital work can enhance public engagement in the humanities.Exploring Big Historical Data should be the go-to resource for undergraduate and graduate students confronted by a vast corpus of data, and researchers encountering these methods for the first time. It will also offer a helping hand to the interested individual seeking to make sense of genealogical data or digitized newspapers, and even the local historical society who are trying to see the value in digitizing their holdings.The companion website to Exploring Big Historical Data can be found at www.themacroscope.org/. On this site you will find code, a discussion forum, essays, and datafiles that accompany this book.
Pensamiento, Pandemia y Big Data
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Este volumen ofrece una cartografía de las reflexiones críticas producidas en el ámbito de la prensa y el pensamiento iberoamericano sobre el impacto social, político, económico y cultural de la pandemia de coronavirus con técnicas y herramientas de análisis del Big Data. A partir de más de 15.000 artículos publicados durante el primer año de pandemia en América Latina y España, el libro propone un estudio cuantitativo y cualitativo por campos epistémicos: i) geopolítico (por países, con especial atención a los del Sur y, por tanto, al replanteamiento de las relaciones Norte-Sur, paralelo al reenfoque de las relaciones Oriente-Occidente); ii) de género (cómo afecta a la mujer, cuerpos feminizados y colectivo LGTBIQ); iii) biopolítico (las principales ideas que han generado los discursos nacionales/transnacionales sobre las regulaciones sociales de nuestras formas de vida y de muerte durante la expansión de esta enfermedad); iv) filosófico-cultural, haciendo balance de los diferentes enfoques desde los que se ha abordado la pandemia de Covid-19, considerando cómo se han modulado en ellos las ideas de humanismo, cultura, arte, sociabilidad, ficción, afectos y otros conceptos del campo de la bioética.
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