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CCT 300: Critical Analysis of Media Class 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.http://48hourfilm.com/)
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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 Signals McAfee, 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 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?
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