We propose as an assistant to virtual communities in conducting a structured discourse on topics of interest.
It supports a top-down group analysis of a subject domain, the accumulation of documentation that supports the process, and the initial stages of a bottom-up development of action proposals (problem solutions).
ConsensUs extends the idea of threaded comment structure by introducing the concept of typed discourse structures and specifying an organization of these structures.
The introduction of organization (internal structure) fosters keeping the community members "on-topic" without sacrificing flexibility. Members are able to pursue ideas in a semi free-form but kept within the domain of interest.
There are two new ideas in ConsensUs that facilitate arrival at consensus, or at least, nuclei of consensus. The first idea is based on learning and memory in brains, specifically short- and long-term Memory Effects.
The second new idea is the use of computational semantic analysis to assist finding common themes and what we will call Nuclei of Consensus.
The central idea is to aggregate and collapse or coalesce comments whose semantic content indicates a high degree of similarity.
Such an aggregation does two things.
It first reduces the Information Load.
Second it provides a Sense of Consensus.