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

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

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

Page 1: 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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Administration

Comic creation marking underway

Get feedback? If not, unlock your wiki!

Feedback cycle should be done by next week, so do the above ASAP.

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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”)

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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

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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?

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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

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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)

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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.

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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

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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

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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…)

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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

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Web 1.0

Web pages as simple publication - “brochureware”

Static content, little to no community participation or input

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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)

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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/

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Another take (Carr)

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

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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

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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)

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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?

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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

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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

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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.

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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?