Summary
*Cultural Analytics* argues that to theorize digital culture, we must first be able to see it, and that given its scale, computers are necessary to achieve this vision. Lev Manovich introduces practical computational tools and methods for scholars to analyze contemporary media, focusing on visual data. The book addresses how to convert cultural processes into computational data and explore these datasets using data visualization and other analytical techniques. Manovich also examines the possibilities and limitations of computational methods in studying culture, and how their use challenges existing scholarly approaches.
The book offers a nontechnical introduction to data science concepts and societal use of data and algorithms, particularly relevant for understanding the vast quantities of digital cultural production. It shifts the focus from "new media" to "more media" by presenting a methodology for analyzing the immense scale of digital culture, such as billions of images and extensive music archives.
Key concepts
- Computational data — Data derived from cultural processes, enabling large-scale analysis.
- Data visualization — A method for exploring and understanding cultural datasets.
- Image and video datasets — Specific types of cultural data analyzed using developed methods.
- Cultural analytics — The field founded by Manovich, providing tools for computational analysis of cultural data.
- "More media" — A conceptual shift recognizing the overwhelming scale of contemporary media production.
From the book
Description: **A book at the intersection of data science and media studies, presenting concepts and methods for computational analysis of cultural data.**
How can we see a billion images? What analytical methods can we bring to bear on the astonishing scale of digital culture—the terabytes of photographs shared on social media every day, the hundreds of millions of songs created by twenty million musicians on Sound Cloud, the content of four billion Pinterest boards? In *Cultural Analytics*, Lev Manovich presents concepts and methods for computational analysis of cultural data, with a particular focus on visual media. Drawing on more than a decade of research and projects from his own lab, Manovich—the founder of the field of cultural analytics—offers a gentle, nontechnical introduction to selected key concepts of data science and discusses the ways that our society uses data and algorithms.
Manovich offers examples of computational cultural analysis and discusses the shift from “new media” to “more media”; explains how to turn cultural processes into computational data; and introduces concepts for exploring cultural datasets using data visualization as well as other recently developed methods for analyzing image and video datasets. He considers both the possibilities and the limitations of computational methods, and how using them challenges our existing ideas about culture and how to study it.