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Total Size:
16.9 MB
Info Hash:
8A1E022F5E2694DAC77866DB100FF0186E39F519
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May 20, 2025, 8:22 a.m.
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(Last updated: May 20, 2025, 8:23 a.m.)
| File | Size |
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| Klinke H. Cultural Data Science. An Introduction to R 2025.pdf | 16.9 MB |
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| Uploaded by andryold1 | Size 16.9 MB | Health [ 52 /33 ] | Added 2025-05-20 |
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NOTE
SOURCE: Klinke H. Cultural Data Science. An Introduction to R 2025
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COVER
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MEDIAINFO
Textbook in PDF format The intersection between humanities, media, and cultural studies and computational methods has become one of the most dynamic areas of research and teaching in universities today. However, as this interdisciplinary paradigm grows, many stu dents and researchers fnd themselves unprepared for the technical demands of cod ing and data analysis. Cultural Data Science: An Introduction to R addresses this challenge with clarity and approachability. Designed as a beginner-friendly resource, this book equips students with the fundamental skills to work with data while grounding their learning in culturally relevant examples from museum collections and art historical archives. Such a low-barrier introduction is precisely what is needed to make computational approaches accessible to a wider audience, empow ering the next generation of scholars to bridge the gap between cultural analysis and data analysis. Harald Klinke is a pioneer in digital art history and cultural data science, having contributed signifcantly to the feld through his research, teaching, and role as co founder of the International Journal for Digital Art History. Through his work, he demonstrates that data science is not just a technical tool but a fundamental approach to understanding cultural phenomena in today's data-rich environment Preface Introduction Setting Up R First Steps First Data Exploring Data Compare Data Case Study 1: Picasso from Creation to Acquisition Subdividing and Combining Datasets Case Study 2: Photography Aspect Ratios Case Study 3: Overview of the MNBAQ Dataset Stacked Bar Plot Working with Images Case Study 4: Image Plot Dimensions Network Visualizations Image Analysis Cloud Computing Epilog: The Future of Cultural Data Science
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