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Contested Collective Intelligence: rationale, technologies, and a human-machine annotation study

De Liddo, Anna; Sándor, Ágnes and Buckingham Shum, Simon (2012). Contested Collective Intelligence: rationale, technologies, and a human-machine annotation study. Computer Supported Cooperative Work (CSCW), 21(4-5) pp. 417–448.

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DOI (Digital Object Identifier) Link: http://dx.doi.org/10.1007/s10606-011-9155-x
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Abstract

We propose the concept of Contested Collective Intelligence (CCI) as a distinctive subset of the broader Collective Intelligence design space. CCI is relevant to the many organizational contexts in which it is important to work with contested knowledge, for instance, due to different intellectual traditions, competing organizational objectives, information overload or ambiguous environmental signals. The CCI challenge is to design sociotechnical infrastructures to augment such organizational capability. Since documents are often the starting points for contested discourse, and discourse markers provide a powerful cue to the presence of claims, contrasting ideas and argumentation, discourse and rhetoric provide an annotation focus in our approach to CCI. Research in sensemaking, computer-supported discourse and rhetorical text analysis motivate a conceptual framework for the combined human and machine annotation of texts with this specific focus. This conception is explored through two tools: a social-semantic web application for human annotation and knowledge mapping (Cohere), plus the discourse analysis component in a textual analysis software tool (Xerox Incremental Parser: XIP). As a step towards an integrated platform, we report a case study in which a document corpus underwent independent human and machine analysis, providing quantitative and qualitative insight into their respective contributions. A promising finding is that significant contributions were signalled by authors via explicit rhetorical moves, which both human analysts and XIP could readily identify. Since working with contested knowledge is at the heart of CCI, the evidence that automatic detection of contrasting ideas in texts is possible through rhetorical discourse analysis is progress towards the effective use of automatic discourse analysis in the CCI framework.

Item Type: Journal Article
Copyright Holders: 2011 Springer
ISSN: 1573-7551
Project Funding Details:
Funded Project NameProject IDFunding Body
Not SetNot SetThe William and Flora Hewlett Foundation
Keywords: collective intelligence; discourse; human annotation; knowledge mapping; machine annotation; learning; sensemaking; network visualization; social software; social annotation
Academic Unit/Department: Knowledge Media Institute
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 31052
Depositing User: Kay Dave
Date Deposited: 25 Jan 2012 10:53
Last Modified: 26 Oct 2012 03:25
URI: http://oro.open.ac.uk/id/eprint/31052
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