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Home NEWS Science News

Lev Manovich’s ‘Cultural Analytics’ is leading the way to understanding digital culture

Bioengineer by Bioengineer
November 9, 2020
in Science News
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New book looks at intersection of data science & media studies, presenting concepts and methods for computational analysis of cultural data

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Credit: The MIT PRESS, 2020.

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 (on sale now from The MIT PRESS), 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.

Cultural Analytics is a book of media theory. Arguing that before we can theorize digital culture, we need to see it, and that, because of its scale, to see it we need computers, Manovich provides scholars with practical tools for studying contemporary media.

The book has received the following glowing endorsements:

  • “Cultural Analytics causes an inspirational mind-shift for the study of culture. Providing key terms and an easy-to-follow non-technical explanation of how to deal with cultural data, it outlines new paradigms in the analysis of data, creation of media visualizations, and eventually the study of culture. Lev Manovich, as always, is leading the way to understanding digital culture.”

    — Harald Klinke, Assistant Professor of Art History, Ludwig Maximilian University of Munich; editor of International Journal for Digital Art History
  • “This is a timely, forward-looking book. It introduces computational algorithms as methods to decode the intricacies of culture. Culture is data waiting to be translated into meaningful patterns by visualization.”

    — Manuel Lima, founder of VisualComplexity.com; author of “The Book of Circles”
  • “Manovich provides a much-needed exploration of how our growing digital world relates to the real one, and how data reflects more than just quantitative insights.”

    — Nathan Yau, founder of FlowingData
  • “Data is fundamentally reshaping the way we create, consume, analyze and visualize content, reshaping our understanding of culture. Manovich, a leading theorist at the intersection of data, arts, and media studies, offers a smart and comprehensive overview of this rapidly changing landscape, documenting the emergence of cultural analytics as a new mode of inquiry.”

    — Albert-László Barabási, Professor of Network Science at Northeastern University; author of “Formula and Linked
    About the Author”

###

Lev Manovich is Professor of Visual Arts, University of California, San Diego. His book “The Language of New Media” (MIT Press, 2001) has been hailed as “the most suggestive and broad ranging media history since Marshall McLuhan.”

Visit his website for more information here: http://manovich.net/

Media Contact
Nicholas DiSabatino
[email protected]

Original Source

https://mitpress.mit.edu/books/cultural-analytics

Tags: Computer ScienceInformation Management/Tracking SystemsLanguage/Linguistics/SpeechLearning/Literacy/ReadingMass MediaSocial/Behavioral Science
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