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Humanities Data In R

, and the humanities and social sciences. Humanities Data with R does not presuppose background programming experience. Early chapters take;

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Scientometrics for the Humanities and Social Sciences

select cases of scientometric studies in the humanities and social sciences, explaining their research objectives, sources of data and;

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Scientometrics for the Humanities and Social Sciences

select cases of scientometric studies in the humanities and social sciences, explaining their research objectives, sources of data and;

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Humanities Data Analysis

A practical guide to data-intensive humanities research using the Python programming language The use of quantitative methods in the;

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Corporate Humanities in Higher Education

How do humanists speak for and from the humanities in an academy which values them less and less and market-driven approaches more and more;

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Corporate Humanities In Higher Education

How do humanists speak for and from the humanities in an academy which values them less and less and market-driven approaches more and more;

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Big Data in the Arts and Humanities: Theory and Practice

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;

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The Data Bonanza

skills to design and develop data-intensive methods and processes. Offering an introduction to the current R and D efforts worldwide, the book;

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Research Methods for Creating and Curating Data in the Digital Humanities

The first volume to focus on digitising and curating data online as research methods for Digital Humanities. In presenting their own;

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The Value of the Humanities in Higher Education

This book presents an extensive analysis of the multifaceted benefits that higher education in the humanities offers individuals and;

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The Digital Arts and Humanities

The case studies in this book illuminate how arts and humanities tropes can aid in contextualizing Digital Arts and Humanities;

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Corpus Linguistics and Statistics with R

methodology and R-based coding from this book teach readers the basic and then more advanced skills to work with large data sets in their linguistics;

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Research Methods

of data and data quality Analysing and organising data to draw sound conclusions Writing up and displaying data in effective ways @text:Complete;

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Spatial Synthesis

science and humanities research has shifted from a data-scarce to a data-rich environment. The chapters also describe how a powerful analytical;

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Applying Language Technology in Humanities Research

, computational linguistics, and natural language processing), and demonstrates how they can be applied by humanities scholars working with textual data;

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Access and Control in Digital Humanities

Access and Control in Digital Humanities explores a range of important questions about who controls data, who is permitted to reproduce or;

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The Digital Humanities Coursebook

The Digital Humanities Coursebook provides critical frameworks for the application of digital humanities tools and platforms, which have;

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The Digital Humanities Coursebook

The Digital Humanities Coursebook provides critical frameworks for the application of digital humanities tools and platforms, which have;

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Digital Humanities

traditionally explored by the humanities. In a world of automation, Big Data, algorithms, Google searches, digital archives, real-time streams and;

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Digital Humanities

traditionally explored by the humanities. In a world of automation, Big Data, algorithms, Google searches, digital archives, real-time streams and;

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Data Analytics in Digital Humanities

, benefited from the open-source sharing not only of data but of code, and made technological capabilities a critical part of humanities work;

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Nietzsche and the Modern Crisis of the Humanities

, offers an alternative paradigm of culture that better fits the data and allows us to understand and defend the humanities as a source of value.;

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Beginning Data Science in R 4

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist;

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Learn R

in the biological sciences, humanities, and many applied fields, recognizing the parallels between R and natural languages should help them feel;

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Learn R

in the biological sciences, humanities, and many applied fields, recognizing the parallels between R and natural languages should help them feel;

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Beginning Data Science in R 4

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist;

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A Computational Approach to Statistical Learning

American Council of Learned Societies (ACLS). His first book, Humanities Data in R, was published in 2015. Michael Kane is an assistant;

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