From our very fruitful collaboration with Ágnes Sándor (Xerox Research Centre Europe, Grenoble), comes this joint journal paper, setting out the conception of Contested Collective Intelligence that we’ve been developing in KMi, as exemplified through Cohere (human social-semantic web annotation and knowledge cartography) plus machine text analysis using Xerox Incremental Parser (mining written text for patterns signifying knowledge level claims and argumentative moves). This article will appear as part of a forthcoming special issue of CSCW journal distilling work from several workshops on collective intelligence in organizations led by Gregorio Convertino:
De Liddo, A., Sándor, Á. and Buckingham Shum, S. (2012, in press). Contested Collective Intelligence: Rationale, Technologies, and a Human-Machine Annotation Study. Computer Supported Cooperative Work. Eprint: http://oro.open.ac.uk/31052
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.