cct 300: critical analysis of media class 9: new media and content creation
TRANSCRIPT
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CCT 300: Critical Analysis of MediaClass 9: New Media and Content Creation
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Administration
Comic creation marking underway
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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?