META/DATA

- A Digital Poetics

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  • E-bog, PDF
  • Engelsk
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Beskrivelse

Blending artist theory, personal memoir, satire, and fictional narratives, a noted net artist constructs a poetics of net art that parallels his practice.This rich collection of writings by pioneering digital artist Mark Amerika mixes (and remixes) personal memoir, net art theory, fictional narrative, satirical reportage, scholarly history, and network-infused language art. META/DATA is a playful, improvisatory, multitrack 'digital sampling' of Amerika's writing from 1993 to 2005 that tells the early history of a net art world 'gone wild' while simultaneously constructing a parallel poetics of net art that complements Amerika's own artistic practice. Unlike other new media artists who may create art to justify their theories, Amerika documents the emergence of new media art forms while he creates them. Presenting a multifaceted view of the digital art scene on subjects ranging from interactive storytelling to net art, live VJing, online curating, and Web publishing, Amerika gives us 'Spontaneous Theories,' 'Distributed Fictions' (including his groundbreaking GRAMMATRON, the helpful 'Insider's Guide to Avant-Garde Capitalism,' and others), the more scholarly 'Academic Remixes,' 'Net Dialogues' (peer-to-peer theoretical explorations with other artists and writers), and the digital salvos of 'Amerika Online' (among them, 'Surf-Sample-Manipulate: Playgiarism on the Net,' 'The Private Life of a Network Publisher,' and satirical thoughts on 'Writing As Hactivism'). META/DATA also features a section of full-color images, including some of Amerika's most well-known and influential works. Provocative, digressive, nomadic, and fun to read, Amerika's texts call to mind the cadences of Gertrude Stein, the Beats, cyberpunk fiction, and even The Daily Show more than they do the usual new media theorizing. META/DATA maps the world of net culture with Amerika as guide and resident artist.

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Detaljer
  • SprogEngelsk
  • Sidetal460
  • Udgivelsesdato18-09-2009
  • ISBN139780262267083
  • Forlag MIT Press
  • FormatPDF

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