Quantitative Methods in the Humanities and Social Sciences – serie

This book highlights the quantitative methods of data mining and information visualization and explores their use in relation to the films and writings of the Russian director, Dziga Vertov. The theoretical basis of the work harkens back to the time when a group of Russian artists and scholars, known as the “formalists,” developed new concepts of how art could be studied and measured. This book brings those ideas to the digital age. One of the central questions the book intends to address is, “How can hypothetical notions in film studies be supported or falsified using empirical data and statistical tools?” The first stage involves manual and computer-assisted annotation of the films, leading to the production of empirical data which is then used for statistical analysis but more importantly for the development of visualizations. Studies of this type furthermore shed light on the field of visual presentation of time-based processes; an area which has its origin in the Russian formalist sphere of the 1920s and which has recently gained new relevance due to technological advances and new possibilities for computer-assisted analysis of large and complex data sets. In order to reach a profound understanding of Vertov and his films, the manual or computer-assisted data analysis must be combined with film-historical knowledge and a study of primary sources. In addition, the status of the surviving film materials and the precise analysis of these materials combined with knowledge of historical film technology provide insight into archival policy and political culture in the Soviet Union in the 1920s and 30s.

This book re-examines the notion of word associations, more precisely collocations. It attempts to come to a potentially more generally applicable definition of collocation and how to best extract, identify and measure collocations. The book highlights the role played by (i) automatic linguistic annotation (part-of-speech tagging, syntactic parsing, etc.), (ii) using semantic criteria to facilitate the identification of collocations, (iii) multi-word structured, instead of the widespread assumption of bipartite collocational structures, for capturing the intricacies of the phenomenon of syntagmatic attraction, (iv) considering collocation and valency as near neighbours in the lexis-grammar continuum and (v) the mathematical properties of statistical association measures in the automatic extraction of collocations from corpora. This book is an ideal guide to the use of statistics in collocation analysis and lexicography, as well as a practical text to the development of skills inthe application of computational lexicography. Lexical Collocation Analysis: Advances and Applications begins with a proposal for integrating both collocational and valency phenomena within the overarching theoretical framework of construction grammar. Next the book makes the case for integrating advances in syntactic parsing and in collocational analysis. Chapter 3 offers an innovative look at complementing corpus data and dictionaries in the identification of specific types of collocations consisting of restricted predicate-argument combinations. This strategy complements corpus collocational data with network analysis techniques applied to dictionary entries. Chapter 4 explains the potential of collocational graphs and networks both as a visualization tool and as an analytical technique. Chapter 5 introduces MERGE (Multi-word Expressions from the Recursive Grouping of Elements), a data-driven approach to the identification and extraction of multi-word expressions from corpora. Finally the book concludes with an analysis and evaluation of factors influencing the performance of collocation extraction methods in parsed corpora.

This book demonstrates how quantitative methods for text analysis can successfully combine with qualitative methods in the study of different disciplines of the Humanities and Social Sciences (HSS). The book focuses on learning about the evolution of ideas of HSS disciplines through a distant reading of the contents conveyed by scientific literature, in order to retrieve the most relevant topics being debated over time. Quantitative methods, statistical techniques and software packages are used to identify and study the main subject matters of a discipline from raw textual data, both in the past and today. The book also deals with the concept of quality of life of words and aims to foster a discussion about the life cycle of scientific ideas.Textual data retrieved from large corpora pose interesting challenges for any data analysis method and today represent a growing area of research in many fields. New problems emerge from the growing availability of large databases and new methods are needed to retrieve significant information from thoselarge information sources. This book can be used to explain how quantitative methods can be part of the research instrumentation and the "toolbox" of scholars of Humanities and Social Sciences. The book contains numerous examples and a description of the main methods in use, with references to literature and available software. Most of the chapters of the book have been written in a non-technical language for HSS researchers without mathematical, computer or statistical backgrounds.

This is the first book to explore prehistoric warfare and violence by integrating qualitative research methods with quantitative, scientific techniques of analysis such as paleopathology, morphometry, wear analysis, and experimental archaeology. It investigates early warfare and violence from the standpoint of four broad interdisciplinary themes: skeletal markers of violence and weapon training; conflict in prehistoric rock-art; the material culture of conflict; and intergroup violence in archaeological discourse. The book has a wide-ranging chronological and geographic scope, from early Neolithic to late Iron Age and from Western Europe to East Asia. It includes world-renowned sites and artefact collections such as the Tollense Valley Bronze Age battlefield (Germany), the UNESCO World Heritage Site at Tanum (Sweden), and the British Museum collection of bronze weaponry from the late Shang period (China). Original case studies are presented in each section by a diverse international authorship.The study of warfare and violence in prehistoric and pre-literate societies has been at the forefront of archaeological debate since the publication of Keeley’s provocative monograph ‘War Before Civilization’ (Oxford 1996). The problem has been approached from a number of standpoints including anthropological and behavioural studies of interpersonal violence, osteological examinations of sharp lesions and blunt-force traumas, wear analysis of ancient weaponry, and field experiments with replica weapons and armour. This research, however, is often confined within the boundaries of the various disciplines and specialist fields. In particular, a gap can often be detected between the research approaches grounded in the humanities and social sciences and those based on the archaeological sciences. The consequence is that, to this day, the subject is dominated by a number of undemonstrated assumptions regarding the nature of warfare, combat, and violence in non-literatesocieties. Moreover, important methodological questions remain unanswered: can we securely distinguish between violence-related and accidental trauma on skeletal remains? To what extent can wear analysis shed light on long-forgotten fighting styles? Can we design meaningful combat tests based on historic martial arts? And can the study of rock-art unlock the social realities of prehistoric warfare? By breaking the mould of entrenched subject boundaries, this edited volume promotes interdisciplinary debate in the study of prehistoric warfare and violence by presenting a number of innovative approaches that integrate qualitative and quantitative methods of research and analysis.

Now in its second edition, Text Analysis with R provides a practical introduction to computational text analysis using the open source programming language R. R is an extremely popular programming language, used throughout the sciences; due to its accessibility, R is now used increasingly in other research areas. In this volume, readers immediately begin working with text, and each chapter examines a new technique or process, allowing readers to obtain a broad exposure to core R procedures and a fundamental understanding of the possibilities of computational text analysis at both the micro and the macro scale. Each chapter builds on its predecessor as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book’s focus is on making the technical palatable and making the technical useful and immediately gratifying.Text Analysis with R is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological toolkit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that readers simply cannot gather using traditional qualitative methods of close reading and human synthesis. This new edition features two new chapters: one that introduces dplyr and tidyr in the context of parsing and analyzing dramatic texts to extract speaker and receiver data, and one on sentiment analysis using the syuzhet package. It is also filled with updated material in every chapter to integrate new developments in the field, current practices in R style, and the use of more efficient algorithms.

Now in its second edition, Text Analysis with R provides a practical introduction to computational text analysis using the open source programming language R. R is an extremely popular programming language, used throughout the sciences; due to its accessibility, R is now used increasingly in other research areas. In this volume, readers immediately begin working with text, and each chapter examines a new technique or process, allowing readers to obtain a broad exposure to core R procedures and a fundamental understanding of the possibilities of computational text analysis at both the micro and the macro scale. Each chapter builds on its predecessor as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book’s focus is on making the technical palatable and making the technical useful and immediately gratifying.Text Analysis with R is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological toolkit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that readers simply cannot gather using traditional qualitative methods of close reading and human synthesis. This new edition features two new chapters: one that introduces dplyr and tidyr in the context of parsing and analyzing dramatic texts to extract speaker and receiver data, and one on sentiment analysis using the syuzhet package. It is also filled with updated material in every chapter to integrate new developments in the field, current practices in R style, and the use of more efficient algorithms.

This textbook introduces graduate students in education and policy research to data and statistical methods in state-level higher education policy analysis. It also serves as a methodological guide to students, practitioners, and researchers who want a clear approach to conducting higher education policy analysis that involves the use of institutional- and state-level secondary data and quantitative methods ranging from descriptive to advanced statistical techniques.  This book is unique in that it introduces readers to various types of data sources and quantitative methods utilized in policy research and in that it demonstrates how results of statistical analyses should be presented to higher education policy makers. It helps to bridge the gap between researchers, policy makers, and practitioners both within education policy and between other fields.Coverage includes identifying pertinent data sources, the creation and management of customized data sets, teaching beginning and advanced statistical methods and analyses, and the presentation of analyses for different audiences (including higher education policy makers).

This textbook introduces graduate students in education and policy research to data and statistical methods in state-level higher education policy analysis. It also serves as a methodological guide to students, practitioners, and researchers who want a clear approach to conducting higher education policy analysis that involves the use of institutional- and state-level secondary data and quantitative methods ranging from descriptive to advanced statistical techniques.  This book is unique in that it introduces readers to various types of data sources and quantitative methods utilized in policy research and in that it demonstrates how results of statistical analyses should be presented to higher education policy makers. It helps to bridge the gap between researchers, policy makers, and practitioners both within education policy and between other fields.Coverage includes identifying pertinent data sources, the creation and management of customized data sets, teaching beginning and advanced statistical methods and analyses, and the presentation of analyses for different audiences (including higher education policy makers).

This book shows how information theory, probability, statistics, mathematics and personal computers can be applied to the exploration of numbers and proportions in music. It brings the methods of scientific and quantitative thinking to questions like: What are the ways of encoding a message in music and how can we be sure of the correct decoding? How do claims of names hidden in the notes of a score stand up to scientific analysis? How many ways are there of obtaining proportions and are they due to chance?After thoroughly exploring the ways of encoding information in music, the ambiguities of numerical alphabets and the words to be found “hidden” in a score, the book presents a novel way of exploring the proportions in a composition with a purpose-built computer program and gives example results from the application of the techniques. These include information theory, combinatorics, probability, hypothesis testing, Monte Carlo simulation and Bayesian networks, presented in an easily understandable form including their development from ancient history through the life and times of J. S. Bach, making connections between science, philosophy, art, architecture, particle physics, calculating machines and artificial intelligence. For the practitioner the book points out the pitfalls of various psychological fallacies and biases and includes succinct points of guidance for anyone involved in this type of research.This book will be useful to anyone who intends to use a scientific approach to the humanities, particularly music, and will appeal to anyone who is interested in the intersection between the arts and science.With a foreword by Ruth Tatlow (Uppsala University), award winning author of Bach’s Numbers: Compositional Proportion and Significance and Bach and the Riddle of the Number Alphabet.“With this study Alan Shepherd opens a much-needed examination of the wide range of mathematical claims that have been made about J. S. Bach's music, offering both tools and methodological cautions with the potential to help clarify old problems.”Daniel R. Melamed, Professor of Music in Musicology, Indiana University

This book shows how information theory, probability, statistics, mathematics and personal computers can be applied to the exploration of numbers and proportions in music. It brings the methods of scientific and quantitative thinking to questions like: What are the ways of encoding a message in music and how can we be sure of the correct decoding? How do claims of names hidden in the notes of a score stand up to scientific analysis? How many ways are there of obtaining proportions and are they due to chance?After thoroughly exploring the ways of encoding information in music, the ambiguities of numerical alphabets and the words to be found “hidden” in a score, the book presents a novel way of exploring the proportions in a composition with a purpose-built computer program and gives example results from the application of the techniques. These include information theory, combinatorics, probability, hypothesis testing, Monte Carlo simulation and Bayesian networks, presented in an easily understandable form including their development from ancient history through the life and times of J. S. Bach, making connections between science, philosophy, art, architecture, particle physics, calculating machines and artificial intelligence. For the practitioner the book points out the pitfalls of various psychological fallacies and biases and includes succinct points of guidance for anyone involved in this type of research.This book will be useful to anyone who intends to use a scientific approach to the humanities, particularly music, and will appeal to anyone who is interested in the intersection between the arts and science.With a foreword by Ruth Tatlow (Uppsala University), award winning author of Bach’s Numbers: Compositional Proportion and Significance and Bach and the Riddle of the Number Alphabet.“With this study Alan Shepherd opens a much-needed examination of the wide range of mathematical claims that have been made about J. S. Bach's music, offering both tools and methodological cautions with the potential to help clarify old problems.”Daniel R. Melamed, Professor of Music in Musicology, Indiana University

This case study-based textbook in multivariate analysis for advanced students in the humanities emphasizes descriptive, exploratory analyses of various types of datasets from a wide range of sub-disciplines, promoting the use of multivariate analysis and illustrating its wide applicability. Fields featured include, but are not limited to, historical agriculture, arts (music and painting), theology, and stylometrics (authorship issues). Most analyses are based on existing data, earlier analysed in published peer-reviewed papers.Four preliminary methodological and statistical chapters provide general technical background to the case studies. The multivariate statistical methods presented and illustrated include data inspection, several varieties of principal component analysis, correspondence analysis, multidimensional scaling, cluster analysis, regression analysis, discriminant analysis, and three-mode analysis.The bulk of the text is taken up by 14 case studies that lean heavily on graphical representations of statistical information such as biplots, using descriptive statistical techniques to support substantive conclusions. Each study features a description of the substantive background to the data, followed by discussion of appropriate multivariate techniques, and detailed results interpreted through graphical illustrations. Each study is concluded with a conceptual summary. Datasets in SPSS are included online.

This case study-based textbook in multivariate analysis for advanced students in the humanities emphasizes descriptive, exploratory analyses of various types of datasets from a wide range of sub-disciplines, promoting the use of multivariate analysis and illustrating its wide applicability. Fields featured include, but are not limited to, historical agriculture, arts (music and painting), theology, and stylometrics (authorship issues). Most analyses are based on existing data, earlier analysed in published peer-reviewed papers.Four preliminary methodological and statistical chapters provide general technical background to the case studies. The multivariate statistical methods presented and illustrated include data inspection, several varieties of principal component analysis, correspondence analysis, multidimensional scaling, cluster analysis, regression analysis, discriminant analysis, and three-mode analysis.The bulk of the text is taken up by 14 case studies that lean heavily on graphical representations of statistical information such as biplots, using descriptive statistical techniques to support substantive conclusions. Each study features a description of the substantive background to the data, followed by discussion of appropriate multivariate techniques, and detailed results interpreted through graphical illustrations. Each study is concluded with a conceptual summary. Datasets in SPSS are included online.

This open-access book surveys how digital technology can contribute effectively to improving our understanding of the past, through a sensory engagement based on the evidence of material culture. In particular, it encourages specialists to consider senses and human agency as important factors in studying ancient space, while recognising the role played by digital tools in enhancing a human-centred form of analysis. Significant advances in archaeological computing, digital methods, and sensory approaches have led archaeologists to rethink strategies and methods for creating narratives of the past. Recent progress in data visualisation and implementation, as well as other nascent digital sensory methods, means that it is now easier to explore and experience ancient space from a multiscalar perspective, from the individual body or single building to the wider landscape.The chapters in Capturing the Senses: Digital Methods for Sensory Archaeologies present innovative methods for representing an embodied experience of ancient space, simulating (but not recreating) ancient behaviours and social interaction. Chapters cover topics including the potentials and pitfalls of visualising, recreating, and re-enacting/experiencing the senses in Virtual Reality environments and also digital reconstructions and auralisations of ancient spaces to study sound sensory perception. Overall, the book demonstrates that multisensory approaches can give a new perspective on how ancient spaces were intended to be used by inhabitants to fulfil a series of purposes including conveying messages and regulating movement.  This is an open-access book.

This open-access book surveys how digital technology can contribute effectively to improving our understanding of the past, through a sensory engagement based on the evidence of material culture. In particular, it encourages specialists to consider senses and human agency as important factors in studying ancient space, while recognising the role played by digital tools in enhancing a human-centred form of analysis. Significant advances in archaeological computing, digital methods, and sensory approaches have led archaeologists to rethink strategies and methods for creating narratives of the past. Recent progress in data visualisation and implementation, as well as other nascent digital sensory methods, means that it is now easier to explore and experience ancient space from a multiscalar perspective, from the individual body or single building to the wider landscape.The chapters in Capturing the Senses: Digital Methods for Sensory Archaeologies present innovative methods for representing an embodied experience of ancient space, simulating (but not recreating) ancient behaviours and social interaction. Chapters cover topics including the potentials and pitfalls of visualising, recreating, and re-enacting/experiencing the senses in Virtual Reality environments and also digital reconstructions and auralisations of ancient spaces to study sound sensory perception. Overall, the book demonstrates that multisensory approaches can give a new perspective on how ancient spaces were intended to be used by inhabitants to fulfil a series of purposes including conveying messages and regulating movement.  This is an open-access book.

This book offers a solution to one of film history’s major controversies: the long-running dispute over Orson Welles’ and Herman J. Mankiewicz’s contributions to the Citizen Kane screenplay. It establishes the vital importance of computing and statistics to solving previously intractable puzzles in the arts and humanities.Citizen Kane (1941) is one of the most acclaimed films in the history of cinema. For 50 years it topped the Sight & Sound film critics’ poll. Orson Welles directed the film and is credited with co-writing the screenplay with Herman J. Mankiewicz. But the co-writer credit generates furious disputes between those who argue Mankiewicz is the sole author of Citizen Kane and those who claim that Welles collaborated fully with its writing. The author employs computing and statistics to answer two questions: What are the distinguishing features of Welles’ and of Mankiewicz’s writing?And What did each contribute to the writing of the Citizen Kane screenplay? To answer these questions, the author bypasses opinions and impressions, and instead subjects the language of the Citizen Kane screenplay to a ‘forensic’ examination. Employing linguistics, basic statistical tests, plus computer technology and software, the author identifies the stylistic signature of each author – the combination of consistent and regular linguistic habits that make each author’s writing distinctive. This book replaces impressionistic discussions of Mankiewicz’s and Welles’ contributions to the Citizen Kane screenplay with a rigorous, experiment-driven statistical analysis. Earlier statistical studies of authorship have discovered that small, unassuming language features (such as punctuation, pronouns, and prepositions) in statistically significant quantities, constitute a screenwriter’s distinctive writing habits. Only with the extensive experimentation carried out in this volume, did the author decide Mankiewicz’s and Welles’ specific habits and their contributions to Citizen Kane.

This book offers a solution to one of film history’s major controversies: the long-running dispute over Orson Welles’ and Herman J. Mankiewicz’s contributions to the Citizen Kane screenplay. It establishes the vital importance of computing and statistics to solving previously intractable puzzles in the arts and humanities.Citizen Kane (1941) is one of the most acclaimed films in the history of cinema. For 50 years it topped the Sight & Sound film critics’ poll. Orson Welles directed the film and is credited with co-writing the screenplay with Herman J. Mankiewicz. But the co-writer credit generates furious disputes between those who argue Mankiewicz is the sole author of Citizen Kane and those who claim that Welles collaborated fully with its writing. The author employs computing and statistics to answer two questions: What are the distinguishing features of Welles’ and of Mankiewicz’s writing?And What did each contribute to the writing of the Citizen Kane screenplay? To answer these questions, the author bypasses opinions and impressions, and instead subjects the language of the Citizen Kane screenplay to a ‘forensic’ examination. Employing linguistics, basic statistical tests, plus computer technology and software, the author identifies the stylistic signature of each author – the combination of consistent and regular linguistic habits that make each author’s writing distinctive. This book replaces impressionistic discussions of Mankiewicz’s and Welles’ contributions to the Citizen Kane screenplay with a rigorous, experiment-driven statistical analysis. Earlier statistical studies of authorship have discovered that small, unassuming language features (such as punctuation, pronouns, and prepositions) in statistically significant quantities, constitute a screenwriter’s distinctive writing habits. Only with the extensive experimentation carried out in this volume, did the author decide Mankiewicz’s and Welles’ specific habits and their contributions to Citizen Kane.

This book discusses in detail a series of examples drawn from scholarly projects that use the OCHRE database platform (Online Cultural and Historical Research Environment). These case studies illustrate the wide range of data that can be managed with this platform and the wide variety of problems solved by OCHRE’s item-based graph data model. The unique features and design principles of the OCHRE platform are explained and justified, helping readers to imagine how the system could be used for their own data.Data generated by studies in the humanities and social sciences is often semi-structured, fragmented, highly variable, and subject to many interpretations, making it difficult to represent adequately in a conventional database. The authors examine commonly used methods of data management in the humanities and offer a compelling argument for a different approach that takes advantage of powerful computational techniques for organizing scholarly information.This book is achallenge to scholars in the humanities and social sciences, asking them to expect more from technology as they pursue their research goals. Written jointly by a software engineer and a research scholar, each with many years of experience in applying database methods to diverse kinds of scholarly data, it shows how scholars can make the most of their existing data while going beyond the limitations of commonly used software tools to represent their objects of study in a more accurate, nuanced, and flexible way.

This book offers an unprecedented quantitative portrait of analytic philosophy focusing on two seemingly marginal features of philosophical texts: citations and acknowledgements in academic publications. Originating from a little network of philosophers based in Oxford, Cambridge, and Vienna, analytic philosophy has become during the Twentieth century a thriving philosophical community with thousands of members worldwide. Leveraging the most advanced techniques from bibliometrics, citations and acknowledgments are used in this book to shed light on both the epistemology and the sociology of this philosophical field, illuminating the intellectual trajectory of analytic philosophy as well as the social characteristics of the analytic community. Special attention is dedicated to the last forty years, providing insights into a phase of analytic philosophy which is still understudied by historians of philosophy.In the eight chapters of the book, readers will find not only numerous quantitative investigations and technical explanations, but also a robust theoretical framework and epistemological reflections on the strengths and limitations of quantitative methods for the study of philosophy. With its strong interdisciplinary appeal, this book will engage a wide range of scholars, including historians of philosophy seeking new methodologies, analytic philosophers interested in a new look at their discipline, and scholars in digital humanities, bibliometrics, and quantitative studies of science, who will find many innovative techniques for investigating disciplinary fields.

This book offers an unprecedented quantitative portrait of analytic philosophy focusing on two seemingly marginal features of philosophical texts: citations and acknowledgements in academic publications. Originating from a little network of philosophers based in Oxford, Cambridge, and Vienna, analytic philosophy has become during the Twentieth century a thriving philosophical community with thousands of members worldwide. Leveraging the most advanced techniques from bibliometrics, citations and acknowledgments are used in this book to shed light on both the epistemology and the sociology of this philosophical field, illuminating the intellectual trajectory of analytic philosophy as well as the social characteristics of the analytic community. Special attention is dedicated to the last forty years, providing insights into a phase of analytic philosophy which is still understudied by historians of philosophy.In the eight chapters of the book, readers will find not only numerous quantitative investigations and technical explanations, but also a robust theoretical framework and epistemological reflections on the strengths and limitations of quantitative methods for the study of philosophy. With its strong interdisciplinary appeal, this book will engage a wide range of scholars, including historians of philosophy seeking new methodologies, analytic philosophers interested in a new look at their discipline, and scholars in digital humanities, bibliometrics, and quantitative studies of science, who will find many innovative techniques for investigating disciplinary fields.

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

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

This book is about the interplay between chance and order, but limited to mostly binary events, such as success/failure as they occur in a diversity of interesting applications. The goal is to entertain and instruct with topics that range from unexpected encounters with chance in everyday experiences, to significant “must know” insights regarding human health and other concerns in the social sciences.The first section provides the tools for being able to discuss random sequences with hints at what is to follow. This is followed by another surprising and, to some extent, bizarre result known as Stein’s Paradox, which is applied to baseball.The troublesome topic of disease clusters, namely to decide whether the clumping of events is due to chance or some environmental cause, is treated using both the Poisson and normal approximations to the binomial distribution and this leads naturally into a discussion of the base rate fallacy and a case study of hospital performance. Next, another medical case study this time concerning some tricky questions about the effectiveness of colonoscopy and other medical interventions. A brief discussion of the mathematics of clinical trials, follows.Then, the book examines the error in random sampling, when polling for candidate preference with specific current examples. The essential tool here is covariance of random variables. The author follows this with a treatment of the spooky quality of coincidence using appropriate mathematical tools. After this, code breaking at Bletchley Park using Baye’s theorem. It returns to Poisson events to discuss another unexpected result, followed by the use of spatial Poisson events in the delivery of emergency response services.Finally, an account of fluctuations that occur in a run of Bernoulli trials as a bookend to the very first section of the book. The probability theory involved is elementary using the binomial theorem and its extensions to Poisson and normal events in addition to conditional probability and covariance. The author provides an optional brief tutorial at the end, that covers the basic ideas in probability and statistics needed in the main text. Besides a list of references, several codes written in Matlab that were used to illustrate various topics in the text, as well as to support several figures that appear throughout, are provided.

This book is about the interplay between chance and order, but limited to mostly binary events, such as success/failure as they occur in a diversity of interesting applications. The goal is to entertain and instruct with topics that range from unexpected encounters with chance in everyday experiences, to significant “must know” insights regarding human health and other concerns in the social sciences.The first section provides the tools for being able to discuss random sequences with hints at what is to follow. This is followed by another surprising and, to some extent, bizarre result known as Stein’s Paradox, which is applied to baseball.The troublesome topic of disease clusters, namely to decide whether the clumping of events is due to chance or some environmental cause, is treated using both the Poisson and normal approximations to the binomial distribution and this leads naturally into a discussion of the base rate fallacy and a case study of hospital performance. Next, another medical case study this time concerning some tricky questions about the effectiveness of colonoscopy and other medical interventions. A brief discussion of the mathematics of clinical trials, follows.Then, the book examines the error in random sampling, when polling for candidate preference with specific current examples. The essential tool here is covariance of random variables. The author follows this with a treatment of the spooky quality of coincidence using appropriate mathematical tools. After this, code breaking at Bletchley Park using Baye’s theorem. It returns to Poisson events to discuss another unexpected result, followed by the use of spatial Poisson events in the delivery of emergency response services.Finally, an account of fluctuations that occur in a run of Bernoulli trials as a bookend to the very first section of the book. The probability theory involved is elementary using the binomial theorem and its extensions to Poisson and normal events in addition to conditional probability and covariance. The author provides an optional brief tutorial at the end, that covers the basic ideas in probability and statistics needed in the main text. Besides a list of references, several codes written in Matlab that were used to illustrate various topics in the text, as well as to support several figures that appear throughout, are provided.

This book addresses growing demand in the visual humanities for foundational knowledge in data analysis, image processing, and artificial intelligence. Intended for readers without prior technical knowledge, its eighteen chapters introduce key concepts in data science through examples from art history, visual computing, and cloud technologies. For advanced readers, it explores how digital methods enhance our understanding of our cultural past. Focusing on image-based humanities research, the book demonstrates practical applications using open source software such as R, RStudio, and ImageMagick, along with       open data sets from institutions like the MoMA, the Met, and the Rijksmuseum.Ideal for students, researchers, and professionals in art history, digital humanities, and museum studies, this book bridges the gap between technology and the humanities, making complex digital methods accessible to a broad audience.

This book addresses growing demand in the visual humanities for foundational knowledge in data analysis, image processing, and artificial intelligence. Intended for readers without prior technical knowledge, its eighteen chapters introduce key concepts in data science through examples from art history, visual computing, and cloud technologies. For advanced readers, it explores how digital methods enhance our understanding of our cultural past. Focusing on image-based humanities research, the book demonstrates practical applications using open source software such as R, RStudio, and ImageMagick, along with       open data sets from institutions like the MoMA, the Met, and the Rijksmuseum.Ideal for students, researchers, and professionals in art history, digital humanities, and museum studies, this book bridges the gap between technology and the humanities, making complex digital methods accessible to a broad audience.

This book teaches R programming for fundamental statistical and data analysis skills, specifically tailored to social scientists and others new to quantitative research. Traditionally, this audience has relied on costly software packages such as SPSS, STATA, and SAS. However, R is a free, open-source alternative that, with proper guidance, is accessible and powerful for their needs. Many existing resources, whether books or online, are overly technical or difficult to follow. This book fills that gap by offering a concise, practical guide to mastering essential statistical processes, equipping readers with skills they can use throughout their careers.Data analysts, institutional researchers, and other professionals will use the book to perform statistical analyses and generate reports for their organizations. The included code—both in the book and online—helps them apply techniques to their own data. Readers will gain the following skills:Install and set up R and RStudio; write R scripts and create R Markdown documents.Understand variable types, measurement scales, and the basics of descriptive and inferential statistics.Conduct chi-square tests, t-tests, ANOVA, regression, and time series analysis in R.Assess and interpret statistical outputs; write results in APA format.Visualize data using ggplot2 and related libraries; create publication-ready charts and tablesEvaluate statistical assumptions and apply techniques responsibly to real-world datasetsCommunicate findings clearly and concisely using professional standards

The Bible's grand narrative about Israel's Exodus from Egypt is central to Biblical religion, Jewish, Christian, and Muslim identity and the formation of the academic disciplines studying the ancient Near East. It has also been a pervasive theme in artistic and popular imagination. Israel's Exodus in Transdisciplinary Perspective is a pioneering work surveying this tradition in unprecedented breadth, combining archaeological discovery, quantitative methodology and close literary reading. Archaeologists, Egyptologists, Biblical Scholars, Computer Scientists, Geoscientists and other experts contribute their diverse approaches in a novel, transdisciplinary consideration of ancient topography, Egyptian and Near Eastern parallels to the Exodus story, the historicity of the Exodus, the interface of the Exodus question with archaeological fieldwork on emergent Israel, the formation of biblical literature, and the cultural memory of the Exodus in ancient Israel and beyond.Thisedited volume contains research presented at the groundbreaking symposium "Out of Egypt: Israel’s Exodus Between Text and Memory, History and Imagination" held in 2013 at the Qualcomm Institute of the University of California, San Diego. The combination of 44 contributions by an international group of scholars from diverse disciplines makes this the first such transdisciplinary study of ancient text and history. In the original conference and with this new volume, revolutionary media, such as a 3D immersive virtual reality environment, impart innovative, Exodus-based research to a wider audience. Out of archaeology, ancient texts, science and technology emerge an up-to-date picture of the Exodus for the 21st Century and a new standard for collaborative research.

This book documents the creation of the Bichitra Online Tagore Variorum, a publicly accessible database of Rabindranath Tagore's complete works in Bengali and English totaling some 140,000 pages of primary material. Chapters cover innovative aspects of the site, all replicable in other projects: a hyperbibliography; a search engine and hyperconcordance working across the database; and a unique collation program comparing variant texts at three levels. There are also chapters on the special problems of processing manuscripts, and on planning the website. Early chapters take readers through the history of the project, an overview of Tagore’s works, and the Bengali writing system with the challenges of adapting it to electronic form. The name Bichitra, meaning "various" in Bengali, alludes both to the great variety of Tagore’s works and to their various stages of composition. Beyond their literary excellence, they are notable for their sheer quantity, the number of variant forms of a great many items, and their afterlife in translation, often the poet’s own. Seldom if ever has the same writer revised his material and recast it across genres on such a scale.​​ Tagore won the Nobel Prize in 1913. By its value-added presentation of this range of material, Bichitra can be a model for future databases covering an author’s complete works or other major corpus of texts. It offers  vastly expanded access to Tagore’s writings, and enables new kinds of research including computational text analysis. The “book of the website” shows in technical and human terms how researchers with interests in art, literature and technology can collaborate on cultural informatics projects.

The Bible's grand narrative about Israel's Exodus from Egypt is central to Biblical religion, Jewish, Christian, and Muslim identity and the formation of the academic disciplines studying the ancient Near East. It has also been a pervasive theme in artistic and popular imagination. Israel's Exodus in Transdisciplinary Perspective is a pioneering work surveying this tradition in unprecedented breadth, combining archaeological discovery, quantitative methodology and close literary reading. Archaeologists, Egyptologists, Biblical Scholars, Computer Scientists, Geoscientists and other experts contribute their diverse approaches in a novel, transdisciplinary consideration of ancient topography, Egyptian and Near Eastern parallels to the Exodus story, the historicity of the Exodus, the interface of the Exodus question with archaeological fieldwork on emergent Israel, the formation of biblical literature, and the cultural memory of the Exodus in ancient Israel and beyond.Thisedited volume contains research presented at the groundbreaking symposium "Out of Egypt: Israel’s Exodus Between Text and Memory, History and Imagination" held in 2013 at the Qualcomm Institute of the University of California, San Diego. The combination of 44 contributions by an international group of scholars from diverse disciplines makes this the first such transdisciplinary study of ancient text and history. In the original conference and with this new volume, revolutionary media, such as a 3D immersive virtual reality environment, impart innovative, Exodus-based research to a wider audience. Out of archaeology, ancient texts, science and technology emerge an up-to-date picture of the Exodus for the 21st Century and a new standard for collaborative research.