Stylistic clusters of Architecture images. Detail.
Our paper compares content, photo techniques and visual styles of 100,000 Instagram images shared in a number of global cities. We use computer vision to detect 1000 types of content and 50 aesthetic features and then compare the images on these dimensions using three different methods.
To visually show the differences in image-sharing by the city’s locals and visitors, we plot the locations of 200,000 images randomly selected from our dataset. See more images on the project web site, Inequaligram.net.
How does a city such as New York is represented in millions of Instagram posts created by locals and visitors? Which parts of a city receive most attention and which remain invisible? How can we quantify and measure these patterns? We investigate these questions using methods from economics and cultural analytics.
50,000 Instagram photos from Tokyo, organized by brightness mean (radius) and hue mean (perimeter). Detail. From the project Phototrails.
Culture Analytics Institute (March 7–June 10, 2016) is bringing together more than 200 computer science and humanities researchers. The use of computational and mathematical techniques to analyze cultural content, trends and patterns is a rapidly developing research area spanning a number of disciplines.
The goal of Culture Analytics program is to present best research and to promote collaborations. To do this, we are bringing together leading scholars in the social sciences, humanities, applied mathematics, engineering, and computer science working on qualitative culture analysis.
The program is organized by Institute for Pure and Applied Mathematics (IPAM), University of California - Los Angeles (UCLA).
Historical examples of "casual photos." Color prints and slides from 1956-1976. Sources: http://look-at-me.tumblr.com/ (submitted vintage personal photos) and https://www.flickr.com (only photos with Creative License are used).
"Professional photos" from Instagram gallery of @neivy (Connecticut, USA) during October-November 2015. 869 posts, 11.7k followers (as of 12/28/2015).
"Designed photos" from Instagram gallery @recklesstonight (Kiev, Ukraine) during October-December 2015. 123 posts, 52.1k followers (as of 12/28/2015).
Lev Manovich, Instagram and Contemporary Image . 25,000 words. Written December, 2015 – November, 2016.
The book is released chapter by chapter on manovich.net during 2016.
Text: Attribution-NonCommercial-NoDerivatives 4.0 International Creative Commons license. Images copyright belongs to their respective authors.
This visualization shows all images that have one or more “Maidan” tags, and every image is repeated for each of its tags. For example, if an image has #euromaidan and #майдан tags, its repeated twice. As a result, 1,340 images turn into 2,917. (The images are organized by date and time (left to right, top to bottom). From research project The Exceptional and the Everyday: 144 Hours in Kyiv (2014), an analysis of Instagram images shared in Kyiv during the 2014 Ukrainian Revolution.
Map of Kyiv that shows locations of images shared during February 18-22, 2014. From research project The Exceptional and the Everyday: 144 Hours in Kyiv.
Detail of research visualizations for the installation On Broadway (2014), an interactive installation exploring the Broadway in NYC using 40 million user-generated images and data points.
Screenshot of the installation On Broadway.
Lev Manovich
The Science of Culture? Social Computing, Digital Humanities and Cultural Analytics (2015).
I define Cultural Analytics as “the analysis of massive cultural data sets and flows using computational and visualization techniques,” I developed this concept in 2005, and in 2007 we established a research lab Software Studies Initiative to start working on practical projects. The following are the examples of theoretical and practical questions that are driving our work.
Radial visualization of 18,941 photographs in the MoMA photography collection. Dates: 1837 - 2012. The distance of a image h from the center is determined by its year of creation; the newer the photograph, the farther it is from the center. The degree of a photograph’s placement in the circle is determined by its average brightness (it increases counterclockwise from 90 degrees).
Visualization of 18,941 photographs in the MoMA photography collection. Dates: 1837 - 2012. Images are sorted by year of creation (vertical axis, ascending from top to bottom).
Nadav Hochman and Lev Manovich. "A View from Above: Exploratory Visualizations of the Thomas Walther Collection," in Mitra Abbaspour, Lee Ann Daffner, and Maria Morris Hambourg, eds. Object:Photo. Modern Photographs: The Thomas Walther Collection 1909–1949. New York: The Museum of Modern Art, 2014.
Nadav Hochman and Lev Manovich, 2013.
The use of quantitative analysis and visualization for the study of cultural visual data allows us to view cultural artifacts in new ways, to confirm and describe more precisely the existing understanding of historical developments, and, potentially, to reveal previously unnoticed patterns. This essay presents visualizations of photographs in the Thomas Walther Collection at The Museum of Modern Art, New York, in relation to the greater MoMA photography collection. To the best of our knowledge, this is the first time that historical patterns in a large photography collection have been analyzed and visualized using quantitative computer techniques.
Media Species poster. Detail. See full size image on Flickr.
Media Species poster. Detail. See full size image on Flickr.
Media Species poster. Detail. See full size image on Flickr.
View a full size image of the poster on Flickr.
Lev Manovich, Sergie Magdalin, Tara Zepel, Kedar Reddy, 2009
Media Species is a poster for SIGGRAPH Info-Aesthetics exhibition in 2009.
The project is comparing different types of media (1930's cartoons, song sequences from Bollywood films, contemporary motion graphics and U.S. TV political ads from 2008) using a variety of visualization techniques.
Visualization 1. Covers of every issue of Time magazine published from the first issue in 1923 to summer 2009. Click here to view the image on Flickr.
Visualization 2. 4535 Time magazine covers are plotted left to right. X axis: Publication date, 1923-2009. Y axis: automatically measured brightness for black and white covers, or saturation for color covers (mean value of all pixels). Click here to view the image on Flickr.
Close-up detail of Visualization 1. Click here to view the full size image on Flickr.
Close-up detail of Visualization 2. Click here to view the full size image on Flickr.
Close-up detail of Visualization 2. Click here to view the full size image on Flickr.
Lev Manovich and Jeremy Douglass
This project presents a visualization analysis of the Time magazine covers (1923-2009).
Data: 128 paintings by Piet Mondrian (1905 - 1917) and 151 paintings by Mark Rothko (1944 - 1957). Mapping: X-axis: brightness mean, Y-axis: saturation mean. This visualization demonstrates how image plots can be used to compare multiple data sets. In this case, the goal is to compare similar number of paintings by Piet Mondrian and Mark Rothko (produced over comparable time periods of 13 years) along particular visual dimensions. See the full size image on Flickr.
Lev Manovich
The visualization (2010) shows 128 paintings by Piet Mondrian (1905-1917) and 123 paintings by Mark Rothko (1938-1953). We have measured selected characteristics (features) of each paintings using image analysis software. In each plot, paintings are organized by average brightness (x-axis) and average saturation (y-axis).
Screenshot of the interactive installation On Broadway.
Interactive installation On Broadway in the exhibition You Are Here NYC: Art, Information, and Mapping, The Pratt Manhattan Gallery, New York City, September 22 – November 15, 2017. Photo: Lev Manovich.
Lev Manovich presents the interactive installation On Broadway at the opening of Data Drift, curated by Lev Manovich, Rasa Smite, and Raitis Smits, Riga, Latvia, October 8 – November 22, 2015. View more photos from the exhibition opening on Flickr. See the installation shots on Flickr.
Interactive installation On Broadway in the exhibition Data Drift, curated by Lev Manovich, Rasa Smite, and Raitis Smits, Riga, Latvia, October 8 – November 22, 2015. View more photos from the exhibition opening on Flickr. See the installation shots on Flickr.
Interactive installation On Broadway in the exhibition Data Drift, curated by Lev Manovich, Rasa Smite, and Raitis Smits, Riga, Latvia, October 8 – November 22, 2015. View more photos from the exhibition opening on Flickr. See the installation shots on Flickr.
Interactive installation On Broadway in the exhibition Public Eye: 175 Years of Sharing Photography, New York Public Library (NYPL), December 13, 2014 - January 3, 2016.
Google Logo Space. Click here to see full 9000 x 6750 version on Flickr.
Close-up: small variations (the right part of the visualization).
Close-up: medium variations (the center part of the visualization).
Close-up: extreme variations (the left part of the visualization).
Jeremy Douglass
Every day billions of people see a new logo appear on Google’s homepage. Since 1998 these logo variations have explored an ever-growing range of design possibilities while still retaining the “essence” of the original logo.
Our visualization of 587 logos shows the space of these variations.
Detail of visualization of 53,498 photos shared in Tokyo taken between 18 and 25 February 2012. Photos are sorted by upload date and time (top to bottom, left to right). Click here for a full size high resolution image.
50,000 Instagram photos from New York City, organized by brightness mean (perimeter) and hue mean (radius). Detail. Click here for a full size high resolution image.
50,000 Instagram photos from Bangkok, organized by hue median (perimeter) and brightness mean (radius). Detail. Click here for a full size high resolution image.
Nadav Hochman, Lev Manovich, and Jay Chow.
Nadav Hochman and Lev Manovich. Zooming into an Instagram City: Reading the local through social media. Feature article, First Monday, July 2013.
What do millions of Instagram photographs tell us about the world?
How can we see larger cultural patterns contained in such massive visual social data?
Do these images reflect the specificity of local places?
A group of researchers from the Art History department at the University of Pittsburgh, the Software Studies Initiative at California Institute for Telecommunication and Information and the Computer Science program at The Graduate Center, City University of New York collaborated to investigate these questions.