By the same authors

Microanalysis of online data: The methodological development of “digital CA”

Research output: Contribution to journalArticle

Published copy (DOI)

Author(s)

  • David Giles
  • Wyke Stommel
  • Trena Paulus
  • Jessica Lester
  • Darren Reed

Department/unit(s)

Publication details

JournalDiscourse, Context, and Media
DateE-pub ahead of print - 29 Dec 2014
DatePublished (current) - Mar 2015
Volume7
Number of pages7
Pages (from-to)45-51
Early online date29/12/14
Original languageEnglish

Abstract

This paper introduces the work of the MOOD (Microanalysis Of Online Data) network, an interdisciplinary association of academic researchers exploring ways of conducting close qualitative analyses of online interaction. Despite the fact that much online interaction meets the criteria for ‘conversation’, conversation analysis (CA) has only recently begun to grow and flourish as a methodology for analysing the overwhelming quantity of material that in many cases sits in archive form, visible to millions, on the Internet. We discuss the development of methods that are inherently suited for subjecting online interaction to the kind of rigorous analysis that conversation analysts have applied to talk of all kinds for several decades. We go on to explore the fundamental challenges that online data pose for CA, the value of many CA techniques for online analysis, and the possibilities of developing bespoke modes of analysis that are crafted for use with specific forms of online data (e.g. ‘tweets’ on Twitter).

    Research areas

  • Online interaction, Conversation analysis, Digital media, Computer-mediated communication, Online discussion

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