Prof. Dr. Lev Manovich

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Fellow Profile

Lev Manovich is a Professor at The Graduate Center at the City University of New York (CUNY) and a Director of the Software Studies Initiative at CUNY and California Institute for Telecommunication and Information (Calit2). He is the author of “Software Takes Command” 2013 (Bloomsbury Academic), “Black Box - White Cube” 2005 (Merve Verlag Berlin), “Soft Cinema DVD” 2005 (The MIT Press), “The Language of New Media” 2001 (The MIT Press), “Metamediji” 2001 (Belgrade), “Tekstura: Russian Essays on Visual Culture” 1993 (Chicago University Press).

 

RESEARCH PROJECT

During my research residency I plan to work on putting together a new book about "cultural analytics." Cultural analytics (http://www.linfo.org/head.html) refers to the analysis of patterns in massive image and video collections using methods from computer science, data visualization and media art, asking theoretical questions that are important for humanities. In 2007 I established a research lab Software Studies Initiative, (softwarestudies.com) at California Institute for Telecommunication and Information (Calit2) to begin this research. The book will present a selection of our practical projects and a few essays covering theory and methodology for using massive visual data in humanities.

Cultural analytics has to address a number of challenging questions. How do we explore patterns in massive visual collections that may contain billions of images and video? How do we research interactive visual media experiences and histories (evolution of web design, playing a video game, etc.)? How to best democratize computer vision and digital image analysis techniques so that researchers and students without technical backgrounds can use them? How can we combine traditional qualitative methods of art history, film and media studies and other humanities and social science disciplines with quantitative image analysis techniques from computer science?

To address these challenges, we developed new methods and software tools and applied them to dozens of data sets covering many types of visual media: TV programs, films, animations, video games, comics, magazines, books, and other print publications, artworks, professional and user-generated photos, etc. (For publications, see (http://lab.softwarestudies.com/p/publications.html).

During first few years, we worked with smaller image and video datasets representing work of professional creators and institutions (for example, digital images of 776 paintings of Vincent van Gogh, or 4535 digital scans of covers of Time magazine 2 published from 1923 to 2009). Gradually, we expanded our research to include larger data sets as well as images shared by semi-professionals (such as amateur artists) and also regular users of social media networks. In one project, we created a dataset of 1 million pages representing complete publications of over 800 manga (Japanese, Korean and Chinese comics) books, processed these images and visualized them to investigate the relations between visual styles of manga and intended audience ages and genders (http://lab.softwarestudies.com/2010/11/one-million-manga-pages.html

).

In another ongoing project, we are analyzing 1 million artworks from www.deviantart.com, the most popular social network for non-professional artists. We have also started working with images from the leading photo-sharing platform Instagram (http://selfiecity.net/, 2014; phototrails.net, 2013). The book will include short descriptions of all these projects and multiple visualizations for each project.