LEV MANOVICH




Cultural Analytics software on 287 megapixel HIPerSpace supervisualization system (YouTube)

Interactive visualization on 287 megapixel HIPerSpace visual supercomputer. The software is developed jointly by Gravity Lab and Software Studies Initiative.

My current research is focused on cultural analytics - the use of computational methods for the analysis of massive cultural data sets and flows. At Software Studies Initiative (my research group) we are working on a particular part of analytics paradigm - using digital image analysis and visualization for working with large visual collections. How we do analyze millions of digitized visual artifacts from the past? How do we explore billions of digital photos and videos (both user-generated content and professional media)? How do we research interactive media processes and experiences (evolution of web design, playing a video game)? To address these challenges, we are developing new methods and software and applying them to progressively larger image and video sets. In addition to digital humanities, these techniques can be also used in cinema studies, game studies, media studies, ethnography, exhibition design, and other fields.

Computational analysis of massive cultural and social data sets and data flows is already used widely in media and web industries. It structures contemporary media universe, cultural production and consumption, and cultural memory. Search engines, Facebook news feeds, spam detection, Netflix and Amazon recommendations, Last.fm, Flickr "interesting" photo rankings, movie success predictions, tools such as Google Books Ngram Viewer, Insights for Search, Search by Image, and and numerous other applications and services all rely on computational analysis of big cultural data. This work is carried out in media industries and in academia by researchers in data mining, social computing, media computing, music information retrieval, computational linguistics, and other areas of computer science.

As humanities and social science researchers start to apply computational techniques to large data sets in their fields (see Digging Into Data 2011 competition), many questions arise. What are the new possibilities for studying culture and society made possible by "big data"? Do humanists and social scientists need to develop their own methodologies for working with big data? What is "data" in the case of interactive media? How can new computational methods can be combined with more established humanities approaches and theories? Is it possibly to study massive media sets without in-depth technical knowledge?

In addition to our practical work, we at Software Studies Initiative are equally interested in exploring such larger questions. We believe that they can only be productively addressed using "software studies" approach, i.e. in depth understanding of software technologies behind cultural analytics.



More information about cultural analytics.

Our visualizations of image and video data (hi-res images on Flickr).

Case studies covering visual art, magazines, books, films, animation, motion graphcs, graphic design, comics, manga.

Free visualization and analysis software tools developed in our lab.

Our publications about about theory and methodology of computational analysis of large cultural data, and our case studies.