How many people in the world use Photoshop?

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Facebook social graph.


How many people in the world use Photoshop? What about Illustrator, Final Cut, Maya, or any other popular media authoring application? How would we make even most approximate estimate? While Adobe, Autodesk, and Apple know how many copies of their software products they sell every quarter, this information is never released. But even if it was, the proportion of people who buy their software vs. all other users is so small that the sales numbers would not help us much.

We know so little about contemporary culture. Its flows, evolutionary mechanisms, patterns of dissemination, reuse, copying, and material bases (such as the number of copies of top software applications which enable it) are not visible to us. It is as though we have our eyes stuck very close to a map - we see few points, but unable to zoom out and see the larger picture.

One area where numbers and maps do exist is the usage of social networks. We know how many blogs are active, how many people use Twitter, how many photos are uploaded to Facebook every month (this number is already over 10 billion); YouTube gives us graphs showing the number of views for every video over time; Google Insights for Search allows us to study the popularity of any search term across time (since 2004) and territories. This is something, but its still limited. It is as though we zoomed out but are only able to see the overall contours on the map defining the areas - but not the details inside. And when some details are made available, they follow the rule of majority - we are told which topics, search terms, videos which are "most popular." These are the tips of the tips of the iceberg, and they are not very interesting. (For example, entering "top searches in the U.S. over 30 days" into Google Insights for Search returns these top items: 1) shoes, 2) samsung, 2) amazon, 4) boots.)

Back to Photoshop. Since late 1990s, I mostly work in cafes - which in Southern California means Starbucks. I am always curious what other people are doing on their computers and tablets around me, and I noticed the following pattern. If I am in a Starbucks and there are at least 10 other people with computers, one of them is using Photoshop. This is an informal observation, and it may only hold for the particular part of San Diego where I leave. But even if the real number is more like 1:20, this is already quite amazing.

What about the places where you live? Did you notice any similar pattern? if we can compare observation, it will give us at least some indication of how many people around the world are engaged in "art" and "design." Would not you want to know this?

I paint data

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Whenever I lecture about our cultural analytics work (computational analysis and visualization of large cultural data), somebody in audience always ask: is this art? Many people who were fed the strict diet of bar chart and pie charts do not know what to think about our visualizations which show large image collections sorted by various visual attributes. Like the individual images they include, these visualizations are colorful, sensual, and aesthetic (i.e. they appeal to senses as opposed to only cognition.) So are they indeed art?

Early in my life i was trained in realist painting and drawing. I had an art teacher in Moscow since I was 12, then went to Moscow Architecture Institute and continued painting for a while after I moved to NYC in 1981. Is it possible that my recent work with visualization of large image collection is a return to painting? Yes - but not just any kind of painting.

Realist art does not capture the world mechanically. Instead, it focuses our attention on patterns in visible world. It highlights some patterns and disregards others. The relations and structures which are highlighted may be color combinations, relations between figures, face expressions, gestures, and so on. These patterns often support the "meaning" of a painting, but not always. (Especially when "modern art" starts to develop in the middle of 1850s, the visual patterns become gradually "liberated" from supporting semantics and meanings.)

Similarly, data visualization reveals some patterns in the data. To do this, data is translated into visual representations, organized in particular ways, and coded using color, shading, size or other graphic attributes.

Both realist art and data visualization are constrained by the data. That is, they don't simply sample some bits of data and arrange in arbitrary combinations. Realist art preserves important aspects of visible reality such as relative sizes of objects and convergence of lines under one point linear perspective, the effects of different types of light sources (e.g., sun casts shadows), etc. Similarly, data visualization preserves (and makes visible) relations in the data set - in contrast to "data art" which may use the same data sets and same representational techniques (e.g., computer graphics) to generate abstract compositions which do not preserve any of the relations in the data.

I can now come back to the question: are our visualizations art? if they are, they belong to the tradition of realist art.

In other words: I "paint" data. But my brushstrokes, colors, and composition are constrained by what is this data. The pleasure which I derive is is following these constraints.

Art always thrived on constraints. Visualization is no difference. Thus, while some of us choose to become data "abstractionists", other prefer to become data "realists." And this is where I am.

Lev Manovich.
2/22/2012.

NYC OccupyData Hackathon uses software tools developed in our lab

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This May Suzanne Tamang used our software tooks in NYC OccupyData Hackathon to visualize Occupy inspired street art. The next Hackathon will take place in September.

Check our Suzanne's work:

is the occupy movement getting more colorful?

Book: Remix Theory The Aesthetics of Sampling

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This book is scheduled to be released in the next few weeks.

Remix Theory: The Aesthetics of Sampling is an analysis of Remix in art, music, and new media. Eduardo Navas argues that Remix, as a form of discourse, affects culture in ways that go beyond the basic recombination of material. His investigation locates the roots of Remix in early forms of mechanical reproduction, in seven stages, beginning in the nineteenth century with the development of the photo camera and the phonograph, leading to contemporary remix culture. This book places particular emphasis on the rise of Remix in music during the 1970s and ‘80s in relation to art and media at the beginning of the twenty-first Century. Navas argues that Remix is a type of binder, a cultural glue—a virus—that informs and supports contemporary culture.

Publisher: Springer Wein New York Press. Official link:
http://www.springer.com/architecture+%26+design/architecture/book/978-3-7091-1262-5
Table of Contents and Introduction are available on the official link.

To get a sense of the content of the book, read an earlier text, also published by Springer, which is now part of chapter three of the book: Regressive and Reflexive Mashups in Samping Culture. Official link to article:http://www.springerlink.com/content/r7r28443320k6012/

Specific case studies for this book are made possible thanks to a post-doctoral fellowship in the Department of Information Science and Media Studies at the University of Bergen, in collaboration with the Software Studies Lab at the University of California, San Diego.

Remix Theory: The Aesthetics of Sampling can now be pre-ordered.  You can place your order on Amazon, Barnes and Nobles, Powell’sl Books, or another major online bookseller in your region, anywhere in the world.  The book is scheduled to be available in Europe in July, 2012 and in the U.S. in September/October of 2012.

The book will also be available electronically through university libraries that have subscriptions with Springer’s online service, Springerlink.  Educators who find the book as a whole, or in part, of use for classes are encouraged to consider the latter option to make the material available to students at an affordable price.

Anyone should be able to preview book chapters on Springerlink once the book is released everywhere.

For all questions, please feel free to contact me at eduardo_at_navasse_dot_net.

Below are selected excerpts from the book:

From Chapter One, Remix[ing] Sampling, page 11:

Before Remix is defined specifically in the late 1960s and ‘70s, it is necessary to trace its cultural development, which will clarify how Remix is informed by modernism and postmodernism at the beginning of the twenty-first century. For this reason, my aim in this chapter is to contextualize Remix’s theoretical framework. This will be done in two parts. The first consists of the three stages of mechanical reproduction, which set the ground for sampling to rise as a meta-activity in the second half of the twentieth century. The three stages are presented with the aim to understand how people engage with mechanical reproduction as media becomes more accessible for manipulation. […]The three stages are then linked to four stages of Remix, which overlap the second and third stage of mechanical reproduction.

From Chapter two, Remix[ing] Music, page 61:

To remix is to compose, and dub was the first stage where this possibility was seen not as an act that promoted genius, but as an act that questioned authorship, creativity, originality, and the economics that supported the discourse behind these terms as stable cultural forms. […] Repetition becomes the privileged mode of production, in which preexisting material is recycled towards new forms of representation. The potential behind this paradigm shift would not become evident until the second stage of Remix in New York City, where the principles explored in dub were further explored in what today is known as turntablism: the looping of small sections of records to create new beats—instrumental loops, on top of which MCs and rappers would freestyle, improvising rhymes. […]

From Chapter Three, Remix[ing] Theory, page 125:

Once the concept of sampling, as understood in music during the ‘70s and ‘80s, was introduced as an activity directly linked to remixing different elements beyond music (and eventually evolved into an influential discourse), appropriation and recycling as concepts changed at the beginning of the twenty-first century; they cannot be considered on the same terms prior to the development of machines specifically design for remixing. This would be equivalent to trying to understand the world in terms of representation prior to the photo camera. Once a specific technology is introduced it eventually develops a discourse that helps to shape cultural anxieties. Remix has done and is currently doing this to concepts of appropriation. Remix has changed how we look at the production of material in terms of combinations. This is what enables Remix to become an aesthetic, a discourse that, like a virus, can move through any cultural area and be progressive and regressive depending on the intentions of the people implementing its principles.

Computational Folkloristics

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A new article from Tim Tangherlini and his UCLA colleagues:

Computational Folkloristics
By James Abello, Peter Broadwell, Timothy R. Tangherlini
Communications of the ACM, Vol. 55 No. 7, Pages 60-70.


Tim Tangherlini organized the most amazing workshop I ever attended: Networks and Network Analysis for the Humanities (An NEH Institute for Advanced Topics in Digital Humanities). Every day we had three lectures from leading experts in network analysis from the academy and also companies such as YouTube, plus hands-on software training. Being able to have lunch with leading people form computer science (who are normally very hard to access) and discuss your project with them was a really unique opportunity. Tim rocks! (Which is more than a metaphor because he really does - in 2002 he produced a documentary "Our Nation. A Korean Punk Rock Community.") His new article is must to read.

nice infographic about social media

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Provided by: Psychologydegree.net

Big Data and Uncertainty in the Humanities

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Big data and uncertainty in the humanities

September 22, 2012,
The Institute for Digital Research in the Humanities,
University of Kansas.

This conference seeks to address the opportunities and challenges humanistic scholars face with the ubiquity and exponential growth of new web-based data sources (e.g. electronic texts, social media, and audiovisual materials) and digital methods (e.g. information visualization, text markup, crowdsourcing metadata).

“Big data” is any dataset that is too large to be analyzable with traditional means (whether e.g. manual close readings or database queries). Developments in cloud computing, data management, and analytics mean that humanists and allied scholars can analyze and visualize larger patterns in big data sets. With these opportunities come the challenges of scale and interpretation; we have moved from the uncertainty resulting from having too little data to the uncertainty implicit in large amounts of data.

What does this mean for how humanists structure, query, analyze and visualize data? How does this change the questions we ask and the interpretations we assign? How do we combine the best of a macro (larger-pattern) and a micro (close reading) approach? And how is interpretative and other uncertainty modeled?

Presentations addressing these both practical and epistemological questions are welcome.