{"product_id":"humanities-data-in-r-exploring-networks-geospatial-data-images-and-text-hardcover","title":"Humanities Data in R: Exploring Networks, Geospatial Data, Images, and Text - Hardcover","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eTaylor Arnold\u003c\/b\u003e (Author), \u003cb\u003eLauren Tilton\u003c\/b\u003e (Author)\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis 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 \u003cem\u003eggplot2\u003c\/em\u003e and \u003cem\u003edplyr\u003c\/em\u003e that center broad data-science concepts.\u003c\/p\u003e \u003cp\u003eThis 2nd edition of\u003cem\u003e Humanities Data with R\u003c\/em\u003e 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.\u003c\/p\u003e \u003cp\u003eEverything 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.\u003c\/p\u003e \u003cp\u003eThe 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.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eTaylor Arnold\u003c\/strong\u003e is Professor of Data Science \u0026amp; Statistics at the University of Richmond and affiliated faculty in the interdisciplinary programs in linguistics and cognitive science. His research applies and develops corpus-based techniques and software to study how messages are communicated through visual and multimodal forms. Arnold is the co-author of four books: \u003cem\u003eHumanities Data in R: Exploring Networks, Geospatial Data, Images and Texts \u003c\/em\u003e(Springer, 2015), \u003cem\u003eA Computational Approach to Statistical Learning\u003c\/em\u003e (CRC Press, 2019), \u003cem\u003eLayered Lives\u003c\/em\u003e (Stanford University Press, 2022), and \u003cem\u003eDistant Viewing: Analyzing Visual Culture at Scale \u003c\/em\u003e(MIT Press, 2023).\u003c\/p\u003e \u003cp\u003e\u003cstrong\u003eLauren Tilton\u003c\/strong\u003e is the E. Claiborne Robins Professor of Liberal Arts and Digital Humanities in the Department of Rhetoric and Communication Studies at the University of Richmond. Her research focuses on 20th and 21st century U.S. visual culture. She is director of \u003cem\u003ePhotogrammar\u003c\/em\u003e, a digital public humanities project mapping New Deal and World War II documentary expression funded by the ACLS and NEH, and author of \u003cem\u003eHumanities Data in R: Exploring Networks, Geospatial Data, Images and Texts\u003c\/em\u003e (Springer, 2015), \u003cem\u003eLayered Lives\u003c\/em\u003e (Stanford University Press, 2022), and \u003cem\u003eDistant Viewing: Analyzing Visual Culture at Scale \u003c\/em\u003e(MIT Press, 2023). Her scholarship has appeared in journals such as \u003cem\u003eAmerican Quarterly\u003c\/em\u003e, \u003cem\u003eArchive Journal\u003c\/em\u003e, \u003cem\u003eDigital Humanities Quarterly\u003c\/em\u003e, and \u003cem\u003eDigital Scholarship in the Humanities\u003c\/em\u003e. She is the co-editor of \u003cem\u003eComputational Humanities (Debates in the Digital Humanities)\u003c\/em\u003e, currently in production with the University of Minnesota Press.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 284\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.69 x 9.21 x 6.14 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e July 23, 2024\u003c\/div\u003e\n            ","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":50314560372973,"sku":"9783031625657","price":178.18,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0020\/8918\/9441\/files\/O68fSxy-2x9783031625657.webp?v=1784663247","url":"https:\/\/www.webster.direct\/products\/humanities-data-in-r-exploring-networks-geospatial-data-images-and-text-hardcover","provider":"Webster.Direct","version":"1.0","type":"link"}