Analyzing the flow of knowledge in computer mediated teams

Joshua Introne, Marcus Drescher

Research output: Chapter in Book/Entry/PoemConference contribution

17 Scopus citations

Abstract

In this article, we present an analysis of communication transcripts from computer-mediated teams that illustrates how different kinds of decision support impact collaborative knowledge construction. Our analysis introduces an algorithmic technique called Topic Evolution Analysis (TEvA), which tracks clusters of words in conversation, and illustrates how these clusters change and merge over time. This analysis is combined with measurements of group dynamics to distinguish between teams using different kinds of decision support. Our analysis offers evidence that some kinds of decision support improve the apparent rationality of a team, but at the cost of collaborative knowledge construction. This result is not apparent when simply measuring team decision performance. We use this finding to motivate the utility and importance of the approach when assessing the impact of technology on collaborative knowledge processing.

Original languageEnglish (US)
Title of host publicationCSCW 2013 - Proceedings of the 2013 ACM Conference on Computer Supported Cooperative Work
Pages341-355
Number of pages15
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 2nd ACM Conference on Computer Supported Cooperative Work, CSCW 2013 - San Antonio, TX, United States
Duration: Feb 23 2013Feb 27 2013

Publication series

NameProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW

Other

Other2013 2nd ACM Conference on Computer Supported Cooperative Work, CSCW 2013
Country/TerritoryUnited States
CitySan Antonio, TX
Period2/23/132/27/13

Keywords

  • Collaborative knowledge construction
  • Computer-mediated communication
  • Decision support
  • Knowledge flow
  • Online conversation
  • Topic tracking

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Networks and Communications

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