CULTURAL ANALYTICS: visualizing cultural patterns
Dr. Lev Manovich Director, Software Studies Initiative, Calit2 + UCSD Professor, Visual Arts Department
email: [email protected] personal web site: www.manovich.net personal blog: databeautiful.net Software Studies Initiative: softwarestudies.com
You can also contact me on Facebook, Myspace, Flickr, and Yourtube.
You can follow the development of Cultural Analytics at http://lab.softwarestudies.com/2008/09/cultural-analytics.html
Friday, November 21, 2008 1 BACKGROUND
Let’s extrapolate and connect some of the most important technological and cultural developments of the last 10 years:
An example of one of the tile displays at Calit2.
Friday, November 21, 2008 2 1| “data revolution.”
Exponential explosion in the amounts of data we generate, capture, and store over last 10 years.
Friday, November 21, 2008 3 By 2011, the digital universe will be 10 times the size it was in 2006. This is a compound annual growth rate of %60.*
------IDC (International Data Corporation). The Diverse and Exploding Information Universe. 2008.
Friday, November 21, 2008 4 2| the rise of interactive visualization: 1988- To deal with information growth and take advantage of news ways to create and capture information, sciences, business, and various social institutions increasingly turned to computer-based analysis and visualization* of large data sets and data flows.
This approach has already yielded significant advances in many scientific fields such as astronomy, geology, genetics, linguistics, environmental science, live sciences, computer science, etc. ------[1] While computers were used for visualization already in the 1960s, the field started to develop rapidly after National Science Foundation (NSF) 1988 report Visualization in Scientific Computing.
Friday, November 21, 2008 5 Example: researchers in the Consortium for Estimating the Circulation and Climate of the Ocean are merging sparse observations of the Southern Ocean with a state-of- the-art ocean circulation model (MITgcm) running on SDSC’s DataStar supercomputer to produce estimates of ocean conditions of greatly increased accuracy. The map shows the speed of the clockwise Antarctic Circumpolar current on May 12, 2006.
Friday, November 21, 2008 6 3| “ data mining society”: appr. 2000-
Friday, November 21, 2008 7 "The next decade will produce a revolution in the use of archived, simulation, and near real-time data to guide future decisions and research directions.”
The Automated Learning Group, National Center for Supercomputing Applications (NCSA) at The University of Illinois.
Friday, November 21, 2008 8 background: beginning to map global culture using “digital traces.” Google Trends.
Friday, November 21, 2008 9 background: beginning to map new global culture using “digital traces.” Blogpulse.
Friday, November 21, 2008 10 Computerworld, May 1, 2006:
Q. Which areas in CS will show the most important and interesting advancements in the next few years?
A. Randal E. Bryant, dean of the school of computer science, Carnegie Mellon University: “A recent big growth area in computing has been in using statistical methods to process vast quantities of data. Google is a prime example of that: They can return a query to you in a few seconds based on the contents of the entire [Web]. How do they do it? By maintaining massive data repositories that allow thousands of processors to operate on terabytes of data. This data-centric style of computing will drive many future efforts in natural-language translation and understanding, astronomy and even epidemiology. For example, we have a project that provides early detection of public health concerns by monitoring the sales of cough and cold remedies at regional pharmacies -- giving a heads-up before doctors start seeing disease trends among their patients.”
Friday, November 21, 2008 11 Statistical analysis of large data sets has become central to many industries, government, and NGOs.
Examples: - business intelligence; - new drugs research; - medical fraud and credit card fraud detection; - anti-terrorism efforts; - customer profiling; - marketing research.
The trend in business intelligence: moving from the analysis of historical data to real-time data analysis.
HP research topic 18 (2008): Real-time Business Intelligence Infrastructure: “For example, an on-line retailer would like to analyze a user’s real-time click stream data and up-to-the-minute inventory to offer dynamically-priced product bundles. A bank would like to detect and react in real-time to fraudulent transactions. A logistics provider would like to dynamically reconfigure shipping routes in response to weather conditions.”
Friday, November 21, 2008 12 While large-scale information visualizations as used in science are still not very common in business, government, and NGOs, they increasingly use other interactive visual tools such as GIS (Geographical Information Systems), Information Dashboards, Perceptual Mapping, etc.
Example of Perceptual Mapping. Consumer perceptions of various automobiles on the two dimensions of sporty/ conservative and distinctive/affordable. Source: en.wikipedia.org/wiki/Perceptual_mapping.
Friday, November 21, 2008 13 4| massive digitization of existing cultural assets
Examples: - Artstor: 7800,000+ high-quality digital images in art and architecture - Google Books: digitizing approximately 3000 books a day - partners include 20 leading university libraries - millions of hours of video in the BBC motion gallery
Friday, November 21, 2008 14 However, our interfaces to vast media collections are still based on 19th century models: a grid of images, a slide show, a timeline, a photo album.
Above: Andre Malraux (future French minister of culture) in the 1920 with his “museum without walls.”
Friday, November 21, 2008 15 5| 2005- The Rise of User-Generated Content
social media sites + software + consumer electronics = social media = “cultural objects produced by non-professional users + conversations around and through these objects.”*
------* Lev Manovich: “The Practice of Everyday (Media) Life.” 2008. Forthcoming in Critical Inquiry.
Friday, November 21, 2008 16 examples of the growth of user-generated content:
Flickr July 2007: 600 million images. Flickr February 2008: 1.2 billion images (100 milion / month).
Facebook: 14,000,000 photo uploads daily.
MySpace: 300,000,000 users.
Cyworld, a Korean site similar to MySpace: 90 percent of South Koreans in their 20s, or 25 percent of the total population of South Korea.
Hi4, a leading social media site Central America: 100,000,000 users.
The number of new videos uploaded to YouTube every 24 hours (as of July 2006): 65,000.
Friday, November 21, 2008 17 The number of images uploaded to Flickr every week is likely to be larger than all objects contained in all art museums in the world.
Friday, November 21, 2008 18 ‘User-generated content” is one of the fastest growing part of the expanding information universe.
“Fast-growing corners of the digital universe include those related to digital TV, surveillance cameras, Internet access in emerging countries, sensor-based applications, datacenters supporting “cloud computing,” and social networks.” *
“Approximately 70% of the digital universe is created by individuals.” *
------* IDC (International Data Corporation). The Diverse and Exploding Information Universe. 2008.
Friday, November 21, 2008 19 6 | parallel expansion of professional cultural universe: agencies (educational institutions, companies, museums), actors (professional cultural producers, students), publishing (books, catalogs, web sites, blogs), cultural objects.
Friday, November 21, 2008 20 The rapid growth of professional educational and cultural institutions in many newly globalized countries along with the instant availability of cultural news over the web has also dramatically increased the number of "culture professionals" who participate in global cultural production and discussions.
Hundreds of thousands of students, artists, designers have now access to the same ideas, information and tools. It is no longer possible to talk about centers and provinces.
In fact, the students, culture professionals, and governments in newly globalized countries are often more ready to embrace latest ideas than their equivalents in "old centers" of world culture.
Friday, November 21, 2008 21 If you want to see this in action, visit the following web sites and note the range of countries from which the authors come from:
student projects on archinect.com/gallery; design portfolios at coroflot.com; motion graphics at xplsv.tv;
Friday, November 21, 2008 22 Friday, November 21, 2008 23 Friday, November 21, 2008 24 growth of a global culture space after 1990. Example: Fashion Weeks, 2005.
Friday, November 21, 2008 25 growth of a global culture space after 1990. Example: architecture. left: Danish Pavillion by MA architects (Beijing), 2006. right: kbh kunsthal in Copenhagen - by MA architects (Beijing), proposal, 2007.
Friday, November 21, 2008 26 Acceleration of changes in consumer behavior. Screenshot from trendwatching.com
Friday, November 21, 2008 27 Before, cultural theorists and historians could generate theories and histories based on small data sets (for instance, "classical Hollywood cinema," "Italian Renaissance," etc.)
But how can we track "global digital culture(s),” with its billions of cultural objects, and hundreds of millions of contributors?
Before you could write about professional culture by following what was going on in a small number of world capitals and schools. But how can we follow the developments in tens of thousands of cities and educational institutions?
Friday, November 21, 2008 28 7 | visualization emerges as a new area of culture: 1998-2007
Friday, November 21, 2008 29 Visualization in public spaces: 2005-
In the last two years visualization has been integrated in some of the most prestigious new buildings: Seattle Public Library (architect: Rem Koolhaus) The New York Times Building in NYC MOMA IAC Building in NYC - lobby (architect: Frank Gerhy), Wolkvagen Autostadt, Germany
Articles about visualization designers and artists - Lisa Strausfeld, Martin Wattenberg, Jonathan Harris - in mainstream press (i.e., Business Week).
MOMA show “Design and Elastic Mind” (Spring 2008) features visualization projects.
Friday, November 21, 2008 30 Visualization of books flow in Seattle Public Library. Artist: George Legrady, UCSB
Friday, November 21, 2008 31 IAC Building, NYC: outside view; the lobby with the visualization showing global users accessing web properties owned by IAC. Dynamic visualization as a new logo of a company/institution -- representation of dynamic process rather than static identity.
Friday, November 21, 2008 32 IAC Building, NYC: lobby with the screen.
Friday, November 21, 2008 33 New York Times building
Friday, November 21, 2008 34 Wolksvagen Autostad
Friday, November 21, 2008 35 a growing number of “artistic” visualization projects: 2005-
Friday, November 21, 2008 36 Friday, November 21, 2008 37 Friday, November 21, 2008 38 Friday, November 21, 2008 39 8 | the rise of “culture visualization”: graphing cultural patterns
culturevis.com - a web site developed by Software Studies Initiative (7/2008 - ) to collect best projects and provide resources for help promote this work.
Friday, November 21, 2008 40 Friday, November 21, 2008 41 Friday, November 21, 2008 42 History Flow visualization
Friday, November 21, 2008 43 History Flow visualization
Friday, November 21, 2008 44 Graphs of statistical data are beginning to be integrated in consumer software and webware. Example: statistics for activity on individual user account on Flickr.
Friday, November 21, 2008 45 Can we create quantitative measures of cultural innovation?
Can we have a real-time detailed interactive maps of global cultural production, consumption, remixing, and collobarations?
Can we visualize flows of cultural ideas, images, and trends?
Can we visually represent how cultural and lifestyle preferences – whether for ideas, music, forms, designs, or products – gradually change over time?
Can we use interactive visualization to research existing cultural trends and patterns and predict their future development?
WELCOME TO CULTURAL ANALYTICS.
Friday, November 21, 2008 46 The joint availability of large cultural data sets (through the exponential growth of user generated content, digitization efforts by museums and libraries, and “digital traces”), cultural information (web presence of all professional cultural agents) and the tools already employed in the sciences to analyze big data makes feasible a new methodology for the study of cultural processes and artifacts - including contemporary cultural production and consumption. We can create interactive visualizations and dynamic maps of large cultural data sets to discover patterns that have not been visible previously.
Friday, November 21, 2008 47 It is time to start thinking of culture as data (including media content and people’s creative and social activities around this content – i.e. social media) that can be mined and visualized.
If data analysis, data mining, and visualization have been adopted by scientists, businesses, and social agencies as a new way to generate knowledge, let us apply the same approach to understanding cultural flows and dynamics.
Friday, November 21, 2008 48 Who would use Cultural Analytics?
- cultural creators in all fields who want to better understand how their work fits within a larger global context - students in digital media, art history, media studies, cultural history, communication studies, ethnography, HCI, etc. - social scientists, historians, anthropologists, humanities scholars who professionally study culture - any researchers who deal with multiple sources of information to study human activity (i.e, video, records of screen activity, movements in space, conversation) - museums and other cultural spaces.
- trend forecasting and cool hunting agencies - marketing and advertising departments of media companies (including social media)
I anticipate that Cultural Analytics systems may eventually be adopted as standard tools in all areas of creative industries – similar to how today most business executives use information dashboards.
Friday, November 21, 2008 49 Cultural Analytics developed by:
Software Studies Initiative - funded by Calit2-San Diego California Institute for Information and Telecommunication) and CRCA (Center for Research in Computing and the Arts, UCSD):
Lev Manovich Jeremy Douglass (post-doctoral researcher) grad and undergrad students in Visual Art Department, UCSD
“Visualizing Cultural Patterns” - 3 year grant from UCSD Chancellor’s Interdisciplinary Collaboratories program:
Lev Manovich, (Calit2- San Diego; Visual Arts Department) Noah Wardrip-Fruin (Calit2-San Diego; Communication Department) James Hollan (Calit2 - San Diego; Cognitive Science) Falko Kuester (Calit2 - San Diego; Department of Structural Engineering)
Friday, November 21, 2008 50 IMAGINE a real-time traffic display (a la car navigation systems) – except that the display is wall-size, and the traffic shown is not cars on highways, but some of the real-time “cultural traffic” around the world.
IMAGINE the same wall-sized display divided into multiple windows, each showing different data about cultural, social, and economic news and trends – thus providing a situational awareness for cultural analysts.
Friday, November 21, 2008 51 IMAGINE a wall-sized interactive visualization showing the long tail of cultural production that allows you to zoom to see each individual product together with rich data about it (à la real estate map on zillow.com) – while the graph is constantly updated in real-time by pulling data from the web.
Friday, November 21, 2008 52 IMAGINE the same wall-sized display playing an animation of what looks like an earthquake simulation produced on a super-computer – except in this case the “earthquake” is the release of a new version of a popular software or an important consumer electronics product, the release of a new major video game, or the announcement of an important architectural project. What we are seeing are the effects of such “cultural earthquake” over time and space.
Friday, November 21, 2008 53 We are building an open Cultural Analytics research environment: an interactive system for the mapping, analysis and visualization of large sets of cultural data and information.
Friday, November 21, 2008 54 “cultural data”: - photos, art, music, design, architecture, films, motion graphics, games, web sites, interactive environments, spaces - i.e. actual cultural artifacts/experiences.
“cultural information” - cultural news published on the web (web sites, blogs);
- both professional and user-generated content; - conversations around cultural content.
Data sets can be comparable in size to largest data sets used in the sciences.
Friday, November 21, 2008 55 Cultural Analytics research environment will run on HIPerSpace OptIPortal, currently (11/2008) the highest-resolution displays in the world - developed @ GRAVITY (Graphics, Visualization and Virtual Reality Laboratory, Calit2-San Diego.)
Calit2 San Diego - HIPerSpace - current configuration: resolution: 287 megapixels (35,640 by 8,000 pixels). physical dimensions: 9.7 metres x 2.3 metres (31.8 feet wide and 7.5 feet). hardware: 18 Dell XPS710 with nVIDIA Quadro FX5600s; 72 Dell 30” Displays.
Calit2 Irvine - HIPerWall - current configuration: 50 Apple 30-inch Cinema Displays driven by 25 Power Mac G5.
The software would run both on a HIPerSpace and on PCs/MACs - although HIPerSpace-type displays offer the ability to see much more detail and also would allow for new modes of interaction with the information (such as group multi-touch).
Friday, November 21, 2008 56 Platform for Cultural Analytics research environment: HIperSpace (287 megapixels).
Friday, November 21, 2008 57 What kind of interface do we need to create “situational awareness” for “cultural analysts”?
The interfaces used today whenever a person/group monitors a performance of system/machine/process, makes decisions and controls (i.e., a “human-machine system) all share the common principle: - multiple displays which present information about a system/process using diff. visual techniques. Examples: vehicle interfaces, patient monitoring in a hospital, control room of a plant, information dashboards, financial news.*
Culture is a complex system / process / environment - therefore we should use similar interface design for studying and monitoring it.
------For a historical analysis of a concept of a “human-machine system,” see Manovich, Engineering of Vision (PhD dissertation, 1993); Manovich and Kratky, Soft Cinema: Navigating the Database (MIT Press, 2005).
Friday, November 21, 2008 58 Text
Example of an existing interface: Barco’s iCommand
Friday, November 21, 2008 59 Example of an existing interface: AT&T control center (2001).
Friday, November 21, 2008 60 Cultural Analytics research environment: interface mockup. Focus: geo map.
Friday, November 21, 2008 61 IDEOLOGY OF DIGITAL TRACES. Not all cultural and social activities leave digital traces on the web. A significant part of today’s global culture is “digitally invisible.” Therefore, we can’t only do projects which rely on web data or existing databases - we also need to take on “digitally invisible” cultural activities using available and original etnographic research. Example: envisioned analysis of the development of “shanty towns” in Mexico city (using research of the local architects working with these communities.)
Friday, November 21, 2008 62 Cultural Analytics research environment: interface mockup. Focus: long tail.
Friday, November 21, 2008 63 Map of Science visualization
Friday, November 21, 2008 64 Cultural Analytics research environment: interface mockup. Focus: relationships map.
Friday, November 21, 2008 65 Cultural Analytics research environment: interface mockup running on HIPerWall
Friday, November 21, 2008 66 Cultural Analytics research environment: interface mockup running on HIPerWall
Friday, November 21, 2008 67 Cultural Analytics research environment: interface mockup running on HIPerWall
Friday, November 21, 2008 68 Example of a use: researchers working with AMVs (Anime Music Video).
Data source: there are a few hundred thousands AMVs available on YouTube and other web sites dedicated to AMVs).
First, the software would analyze all videos extracting various features. This metadata will be added to previously available metadata: descriptions and rating by authors and fans, place of origin, video length, year, etc.
The interactive system would allow us to see each video in the context of the overall set; identify "statistically improbable" videos; add/edit our own metadata, descriptions, markers, etc. We can also simultaneously display the remix videos and all the sources they use and analyze the relationships. We would also be able to compare the analytical languages by authors, fans, and professional researchers (if we collect the appropriate data first).
Friday, November 21, 2008 69 Why “Cultural Analytics”?
existing terms: “knowledge discovery” “from data to knowledge”
“web analytics” “business analytics” visual analytics = “the science of analytical reasoning facilitated by interactive visual interfaces”
Friday, November 21, 2008 70 On April 22, 2008, National Endowment for Humanities Office of Digital Humanities announced Humanities High Performance Computing initiative:
“Humanities High-Performance Computing (HHPC) refers to the use of high- performance machines for humanities and social science projects. Currently, only a small number of humanities scholars are taking advantage of high-performance computing. But just as the sciences have, over time, begun to tap the enormous potential of HPC, the humanities are beginning to as well. Humanities scholars often deal with large sets of unstructured data. This might take the form of historical newspapers, books, election data, archaeological fragments, audio or video contents, or a host of others. HHPC offers the humanist opportunities to sort through, mine, and better understand and visualize this data.”
NEH wants humanists to get trained to use TeraGrid network and the National Energy Research Scientific Computing Center (NERSC) at the Lawrence Berkeley National Laboratory. Currently, TeraGrid resources include more than 750 teraflops of computing capability and more than 30 petabytes of online and archival data storage.
Friday, November 21, 2008 71 November 20, 2008: Software Studies Initiative is awarded Humanities High Performance Computing initiative grant.
The grant will be used to analyze and visualize large visual media data sets (photographs, video, films, videos of gameplay, etc.)
Friday, November 21, 2008 72 While Humanities High-performance Computing initiative (HHPC) so far has been only announced in the USA, we can expect that the idea of data mining and visualizing large humanities and social science data sets will soon be taken in other countries.
Our goal is to create a general-purpose Cultural Analytics research environment which could be used by not only us but also all other researchers working with large cultural data sets.
At the same time, while we also want to data-mine cultural data from the past, the goal of Software Studies Initiative is to work on analyzing and mapping contemporary global cultural production, consumption, remixing, collaboration, preferences, dynamics, flows, and patterns.
Friday, November 21, 2008 73 Cultural Analytics in the classroom
Cultural Analytics is very suitable for undergraduate teaching. Because data gathering, data analysis, and visualization can be treated as separate projects, the work can be continued across the semester boundaries. For instance, students in one class can work on visualizing data sets created by students in a previous class. (I have already been using this approach in my classes using ManyEyes.)
Cultural Analytics Research Environment can also act as a global educational platform. We envision students from around the world contributing data sets, maps and visualizations, analyzing each other data, etc.
Friday, November 21, 2008 74 Example of a student project done at UCSD (winter 2008): a visualization of the connections between subcultures. source: sharedeggg.blogspot.com
Friday, November 21, 2008 75 Friday, November 21, 2008 76 “casual” “trendy”
Friday, November 21, 2008 77 Key differences between existing work in culture visualization and our approach:
1. The projects created so far are driven by the available data rather than by theories of cultural and social processes. We believe that significant results will only be achieved in the context of theoretical research questions from the humanities, social sciences and culture industries combined with the advances in information visualization and interaction design.
2. Existing cultural visualizations typically use relatively small data sets. We want to develop new visualizations and interaction techniques appropriate for much larger data sets. The limitations of existing visualizations are, in part, an outgrowth of the fact that many are designed for the web, limiting how much information they can show legibly. We will use new wall-size displays with a resolution in hundreds of megapixels to display more information and also to enable new modes of interaction (such as HiperWall and HiperSpace created at Calit2). This will also allow us to address the challenge of analyzing and visualizing data-intensive types of cultural media that so far have not been approached - specifically, feature films, video, computer games, and architecture.
Friday, November 21, 2008 78 3. Most existing work in visualization of media data relies exclusively on existing metadata (such as Flickr community-contributed tags). In contrast, our methodology calls for the computational content analysis to generate new metadata - in particular, image processing and computer vision.
4. The existing culture vis projects typically show the abstract graphs - but not the original data. Cultural Analytics research environment which will allow the user to work both with the original data and its multiple visualizations at the same time. When a user makes a selection in one display, all displas are automatically updated. The interface also allows the user to move between the overall view of the whole data set and the individual cultural artifacts.
5. Cultural Analytics research environment will be an open social knowledge production platform. Users will be able to add new analytical and visualization modules. We can also use collaborative knowledge production / social media paradigm: users can add their own data, analysis of data, visualizations, interpretation of the results created by others, vote for most interesting results, etc. Study of culture moves from being the domain of small groups of experts to being open to all. We can also tap into the knowledge of millions of fans and passionate users - they can annotate cultural objects they are knowledgible about, judge if visualizations and analysis make sense to them, etc.
Friday, November 21, 2008 79 6. Existing culture vis projects usually show only a few or a single dimensions of a data set.* Our methodology is to visualize separately each of the dimensions of a data set (and some of their combinations if appropriate) and to combine these visualizations into a single intergrated interactive interface.
------* a “dimension” = a record’s field in a cultural database, i.e. author’s name, project date, shape, distribution of colors, etc.
Friday, November 21, 2008 80 Examples of projects we want to do within Cultural Analytics paradigm: Projects which analyze the contents of a set of cultural products (each questions below can be also asked in relation to any other art/design field) in order to visualize historical development, influences, differences, etc.: (1) Are there any differences today between portfolios of designers (in a particular field) from different countries? If so, how significant are these differences? How did this changed over last 10 years?" (Examples of data sets: design portfolios on coroflot.com; student blogs of architectural schools @ archinect.com, short films on vimeo, etc.) (2) If we describe contemporary motion graphics (or any other art/design field) works using a number of attributes, what patterns can we observe if we sample a large number of works? Do some attributes tend to occur together? Are there any significant differences today between the works in different genres - commercial, experimental, VJ live, etc?"
Friday, November 21, 2008 81 More examples of visualization projects showing cultural dynamics - the patterns in how cultures change:
(3) If we graph the gradual simplification of forms in European art of the end of the nineteenth and early twentieth century which eventually lead to pure abstraction, what patterns can be observe? Will we see a linear development (i.e. a strait line) or will we see some jumps, accelerations, etc.? Will these patterns be different for different arts and media (i.e., painting, furniture, decorative arts, architecture)? We can also do this project in relation to the characteristics of video games, movies, blogs, or any other currently popular cultural form over periods of time. (4) the story of how the world has moved from a “old world” paradigm to a “flat world” (2000) to an ”inverted world” (2005) in which “newly developed countries” have become leaders in cultural innovaton and experimentation? (5) Cultural evolution - the ways in which a set of cultural forms gives rize to more forms - for instance, a visualization showing the proliferation of styles in popular and dance music over the last few decades and their adoption around the world; 6) Mapping cultural and social phenomena which do not leave easily accessible “digital traces” on the web - for instance, a time-space interface showing the growth of “shanty towns” in Mexico city (small towns developed by people themselves from scratch over a few decades - “DIY urbanism.”)
Friday, November 21, 2008 82 Examples of projects which look at the patterns in the development of cultural institutions, ideas, and cultural perceptions:
(7) How do designers in different parts of Asia incorporate the concept of “Asia” in their designs? Do these different “Asia” concepts work in distinct ways in different media? What are the “cultural DNA” which make “Asia” in design, and how they are distributed across different regions, media, markets? (8) What geopolitical patterns would we see if we map the growth of art museums (or: art biennials, design biennials, fashion works, film festivals, design schools, university programs in media, university majors for new subjects, publications in art history, articles on media art, etc.) around the world over last decade? What patterns would we see if we analyze the titles and descriptions of all the exhibitions they have put on?
(9) If we look at new cultural concepts (or selected set of concepts) which emerged in this decade, how much attention and "mindshare" these concepts have captured relative to each other? To answer this question we can analyze Wikipedia pages for these concepts. We can use the dates when the pages were established and also compare how much and how frequently people contributed to each page." (I.e., doing History Flow type of analysis - but on a large set of wikipedia pages.)
Friday, November 21, 2008 83 Examples of a projects which analyze cultural flows - the ways in which “cultural atoms” (elements, memes) and “cultural DNAs” (techniques) travel in time, space and from one context to another:
10) How does a new cultural atom travels in space, time, and gets adopted by other subcultures/authors? For instance, what patterns would we see if we map and analyze how the elements of the new popular video gets remixed by other users in their videos?
11) Can we map the relationships between AMVs produced by fans and all original sources they use (anime, music videos, computer games)?
12) Since the history of human cultures is that of cross-cultural exchange, adoptation, and intergration of foreign elements into the existing culture - can we create detailed visualizations of such flows based on the content analysis of large number of artifacts? Example: development of modern art in diff. Asian countries in the 20th century - attempts to integrate Western ideas with the local traditions. Example: a study of material artifacts from a number of ancient cultures which were in contact. Example: beginning with the artifacts in a culture in a particular place and time period, we “crawl” (a la web search engine) to all other cultures which these artifacts historically are connected with (came from).
Friday, November 21, 2008 84 fMRI of a global “cultural brain”
today neuroscience combines single neuron recodings, tracking activities of neural networks (1mm) and neural maps (1cm), fMRI of the neural activity of the whole brain, and other methods.
Usual analysis of culture can be compared to recording and analyzing activity of a single cell or a small cell population. We need to start tracking, analyzing and visualizing larger cultural structures - (including their connectivity and dynamics over space and time) - equivalents of neural networks, maps, cortical columns, and the whole brain.
Applying other techniques from neuroscience such as staining cells. (UCSD + other research labs nearby - the leading area in the world for neuroscience research).
Applying the basic method of contemporary neuroscience: combining results from different research methods (MRI, PET, staining cells, genomics, etc.)
Friday, November 21, 2008 85 P.S. Our long-term research plans:
from visualization of cultural patterns to modeling and simulation.
Friday, November 21, 2008 86 Studying cultural processes: from taxonomy to evolutionary biology
We usually think of culture in terms of taxonomies - styles, genres, market segments - equivalent of the biology in the 18th century.
The exponential increases in the number of cultural objects (lifestyle products, films, photographs, songs, graphic designs, etc.) created by both professional producers and non-professionals - and the similar increase in the number of producers - create a new cultural universe.
The sheer size of the new cultural universe, and its much higher connectivity[1] makes appropriate to apply scientific paradigms and methods (including mathematical models and computational modeling) used in evolutionary biology, environmental biology, genomics, bioinformatics, and other live sciences to study large-scale biological phenomena. [2]
------
[2] Future collaboration with Calit2 Center for Algorithmic and Systems Biology (CASB)
Friday, November 21, 2008 87 ------[1] Higher cultural connectivity: “globalization”: access to the same ideas and tools + more people using English as a global cultural platform; large-scale globally distributed production in games industry, film industry, etc.; social media software which encourages remix and “media mobility”*; desktop software production environment which similarly makes it very easy to borrow elements from other cultural products; increase in travel; access to cultural objects produced by everybody else (Youtube, Flickr, portfolio web sites of professional designers, etc.)
* Lev Manovich, “Remixability and Modularity,” 2005.
Friday, November 21, 2008 88 Mathematical simulations of global cultural flows based on the existing data?
Blue Brain project @Henry Markram's Brain and Mind Institute at the École Polytechnique (EPFL) in Lausanne *
Henry Markram anticipates that a simulation of a complete human brain down to the molecular level (based on all existing experimental neuroscience data) will be available before 2020.
Friday, November 21, 2008 89 ------* An interdisciplinary team of 35 researchers has cast the reverse-engineering of the biological pieces and the forward construction of detailed mathematical models in an iterative process that allows continuous refinement. Particular efforts go into the preparation of 10,000 unique morphologically-complex electrical models representing all morpho-electrical classes as well as establishing their structural and functional connectivity. Once a multi-compartmental description for each neuron is generated and the exact locations of the synapses (~30 million) are determined, the simulation is supposed to reproduce emergent properties found in slice experiments. The refinement is directed by a bottom-up calibration that aligns the model across all levels - from the ion channels to the emergent network phenomena - with the experimental data. In order to put the expert in the loop, extensive use of visualization and interactive analysis is made, which is powered by another dedicated supercomputer in order to realize short turn-around times.
Friday, November 21, 2008 90 If we do simulation-based research into global cultural flows, what kinds of models would we need? More complex than for brain simulation? More simple?
If simulation-based research is now being applied to new scientific areas, let us use it to study global culture.
What new analytical categories can we develop if we aim for an equivalent of a Blue Brain project - simulating all of contemporary global cultural developments and relationships using all available data?
Friday, November 21, 2008 91