CCT 300: Critical Analysis of Media Class 9: New Media and Content Creation.

CCT 300: Critical Analysis of MediaClass 9: New Media and Content Creation

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Manovich’s LNM

Language of New Media - distilling the core essence of new media into eight propositions

More of a media form/genre definition

N.B. “New Media” is not a chronological term (although contemporary media are more likely to be “new”)

New Media vs. Cyberculture

Proposes a distinction - new media studies forms and codes vs. social effect (e.g., media use studies, cultural studies…)

Acknowledges cyberculture as interesting but a different field entirely

New Media as Distribution

Looks at new media explicitly as channel - digital transmission, in whatever form

Representation in digital form is increasingly common - examples?

Limitations of this approach?

New Media as Software Controlled Use of data structures, modularity, automation to create

the cultural form

Digital photography/video as example; due to common technical standards for coding and manipulation, media objects can be shared and manipulated (sometimes automatically) with ease

Other examples - e.g., dynamic web pages, Google AdSense

Cultural conventions

Uneven development - just because you can represent and manipulate something in digital form doesn’t mean it will work will in practice (e.g., digital actors?)

“morph” or “composite” - earlier conceptual models survive transition to new media and impact its form (e.g., desktop metaphor vs. alternatives)

Aesthetics of New Media

New media technologies create their own established aesthetics

Example: DV movies and cheaper amateur production (e.g., http://48hourfilm.com/), YouTube, vblogging, etc.

New Media as Efficient

Computing technology executes various tasks considerably faster - e.g., 3D animation, composite photography

Efficiency opens up new possibilities that were not present before

New Media as Metamedia

New media repurposes old media, combines existing media sources (e.g., photo montage, mashups, music sampling)

Not a new phenomenon, (e.g., collage, 1920s avant-garde film) but much easier done with digital objects

New Media as Nexus of Art and Computing

Computing becomes a more right-brain, creative process - a tool to represent and create new realities vs. simply crunch numbers (although there’s lots of that still required…)

Internet as New Media

Certainly efficient metamedia

Also envelops previous forms of content/conventions

Increasingly software controlled (e.g., static vs. dynamic pages)

Webcomics show nexus of art/computing and value of digital production/distribution

Web 1.0

Web pages as simple publication - “brochureware”

Static content, little to no community participation or input

1.0 -> 2.0

Introduction of community and data management systems

Leveraging power of social networks

Data-driven content - dynamic page creation

Data manipulation and creation by users

Democratic, open-source generally

“social” web (and version 3.0 = semantic web)

SLATES (McAfee)

Search

Linking

Authorship

Tagging

Extensions

SignalsMcAfee, A.P (2006). Enterprise 2.0: The Dawn of Emergent Collaboration. Sloan Management Review, 47(3), 21-6. http://sloanreview.mit.edu/smr/issue/2006/spring/06/

Another take (Carr)

Carr, A. (2007). Designing for Sustainable Conversations. InteractionCamp 2007.http://www.slideshare.net/acarr/designing-sustainable-conversations-with-social-media-59204

Driving traffic through social media

How do you leverage social media to popularize content?

*not* just technology – build it, they won’t come. Why?

The role of content aggregators (e.g., 4chan, digg, reddit, KYM, Buzzfeed, StumbleUpon etc.) – reintermediation in content/audience dynamic

Web analytics basics

Data-driven web = data footprints everywhere

Data passed on by every web call: IP address, platform, browser, referral page

Allows for custom content (e.g., vague geolocation data, customization for plattorm (esp. mobile), content specific to source (e.g., welcoming visitors from particular sources)

Server/client interactions

HTTP as stateless (implications?)

Cookies – information passed on in web calls for session/continued use

Detailed information can be embedded to support future interaction

Implications of this?

Integration of subscriber data

Registration for social media services – what information is sometimes requested?

Profile -> action link interesting and valuable

Facebook as advertising platform -> why would subscriber data be especially valuable in FB?

Youtube analytics – age info likely from profile

Search Engine Optimization (SEO)

How do you get to Page 1 of Google?

Can (and should) happen naturally, but underhanded/unethical techniques common (examples?)

A better technique: create good content

http://igniteshow.com/videos/oatmeal-how-get-5-million-people-read-your-website-ep-69

Online advertising

Advertising = not really viral

Google Adwords = targeted to keyword searches, location

Facebook ads = potentially targeted to a range of other interests

More on all this? Take CCT356.

Weekly assignment

http://www.google.com/analytics/tour.html

What information could you learn about viewers of your meme using such a tool?

How could this information be valuable in refining meme and its propagation?