Week 2 Slidecast: Networked Information

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    Week 2 Slidecast: Networked Information - Presentation Transcript

    1. Networked Information KCB201 Virtual Cultures Dr Axel Bruns [email_address]
    2. Visions of the Network Age
      • Vannevar Bush’s vision:
        • Technology aiding us
          • in navigating the information available to us, and
          • storing (and sharing) the knowledge we accumulate.
          • (Technology as driver, determining what people are able to do.)
      • Mark Pesce’s vision:
        • People using technology
          • to develop new ways of being, of communicating, of knowing, and
          • to change culture, society, the world.
          • (People as drivers, enabled by technology.)
        • Reality?
      • technological determinism social constructionism
    3. New Media Technologies
      • Three elements to keep in mind:
        • the technologies themselves, and their in-built features
        • the communication activities and practices we engage in using these technologies
        • the social arrangements that form around these technologies
        • (Flew p. 2)
      • Key features of information in new media:
        • manipulable – digital format makes editing simple
        • networkable – transmission and sharing on a global scale
        • dense – even large amounts can be transmitted quickly
        • compressible – enabling duplication and storage of large amounts
        • impartial – networks transmit both trash and treasure equally well
        • (Flew p. 3)
    4. A Time of Change
      • Entering the information age:
        • shift from analogue to digital
        • emergence of global information networks (wired and wireless)
        • transition from manufacturing to information, knowledge, creative industries (in developed nations)
        • economic, political, media globalisation
        • convergence on various levels
        • online communities, networked social structures
        • bottom-up, ad hoc network organisations
        • unexpected consequences of information availability and flexibility
        • alternative sources of information and knowledge
        • undermining of established power structures
        • struggle for control of the network, of information, of meaning
    5. Networked Information
      • Competing logics of information:
        • traditional model:
          • core information produced by established institutions in society
            • governments, researchers, industries, media
          • internal processes determine what is released and what is not
          • information can be trusted because it has an institutional imprint
          • information is evaluated and ordered by professionals with expert knowledge
          • examples: publishers, libraries
        • network model:
          • information produced by all of us, and published immediately
            • personal blogs, YouTube clips, Wikipedia entries, etc.
          • ‘ official’ and ‘unofficial’ information co-exist in the network, and are equally easy to find
          • can any piece of information be trusted? user must decide for themselves
          • information is evaluated by all of us, all the time – and we’re sharing those evaluations
          • examples: Google , del.icio.us
        • expert power  people power or academic logic  Google logic
    6. Making Sense of Networked Information
      • New survival skills:
        • finding, evaluating, sharing (and trusting that others do so too)
          • finding a Website through Google, del.icio.us, recommendation from peers
          • evaluating its usefulness, describing and tagging it for future reference
          • sharing that evaluation through del.icio.us or other social networks
        • keeping track of what others find, evaluate, share
          • finding communities of like-minded users
          • collaborating with them on finding information
          • (and filtering out disruptions to the process)
      • Google logic:
        • measuring importance and relevance of information by tracing patterns in large-scale user behaviours
          • … and it works – Google PageRank
        • but where does this leave the traditional knowledge institutions?

    + Axel BrunsAxel Bruns, 2 years ago

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