ConsensUs: An Asynchronous, Collaborative,
Deliberative, Structured, Discourse System
George Mobus
University of Washington – Tacoma
One of the most pressing needs for modern, global society is for a scalable discourse
system that will support social problem solving. Such a system will allow any and all
who wish to contribute to international discussions on global problems (e.g., global
warming and climate change) to do so.
ConsensUs has been proposed as a global-scale computer-mediated communications
system that enhances deliberative, collaborative discourse in an asynchronous forum.
The system’s architecture provides a natural, top-down analysis of problems in the form
of a topic-subtopic tree structure. Associated with each topic (or subject) are sets of
‘issues’ or questions that need to be resolved further, comments on the topic and related
to the issues, and proposals, which relate to methods for investigation or methods for
solving the problem identified at the current level of topic in the tree. ConsensUs
naturally guides users to decompose a problem into sub-problems and then build
proposals for solutions in a bottom-up manner. This system boasts three fundamental
features that allow it to achieve these ends.
The first feature is the organization of discourse objects that allow the management of the
discourse and provide a visual representation (actually several) for user navigation.
Discourse is categorized into four basic kinds of objects: Topics (and subtopics), Issues,
Comments, and Proposals. A fifth object type, User-defined, allows for extensibility. The
tree is organized around the Topic-Subtopic structure. All other objects are attached as
children of a topic node (subtopics are topic nodes). Thus a tree level in ConsensUs is
composed of subtopics, issues, comments, and proposal. Both issue and proposal objects
can also have comment children nodes, but no other kind. The discourse process is thus
guided by what can be said, a subtopic asserted, a question posed, a comment made, or a
proposal put forward, at any given level in the topic tree. It is also guided by how these
items are said in that each object is identified by one of these types. Finally, it is guided
in terms of supporting (indeed, largely enforcing) a top-down decomposition process. We
feel this structure will produce a highly efficient process of open discourse. It will help
users organize their thinking and keep discussions on topic and on track toward a goal.
Discourse has had the problem of scaling to the size of the problem domains when the
number of discussants needed to pursue solutions in those domains has grown very large.
An obvious problem is the sheer number of discourse objects that will get created and the
ensuing magnitude of the tree structure. This leads to the second feature of ConsensUs.
In order to manage the complexity of the topic tree and its nodes, we propose to use two
computational intelligence techniques. The first is designed to aid users in understanding
the overall semantic content of the tree structure. We propose to use a Latent Semantic
Analysis (LSA) method to collapse a collection of tree nodes into a semantically
representative node (the ‘centroid’ of a cluster of commentaries) as a consensus develops
over the topics, issues, comments, and proposals. This will be especially useful in
managing comments where we imagine large numbers of comment nodes will be
subsumed under a single best representative comment thus appearing to prune the tree
and making the discussion much easier for users to digest the semantics of the topic.
The second method employs a type of learning or memory trace mechanism that keeps
track of the activity below a particular node on the tree. Once a user publishes an item in
the tree (except comments, which have no children nodes) it gets an amount of time to
live that declines if there is no activity from other users in the form of additional children
nodes being added. On the other hand, if there is sufficient interest in the item, the time is
incremented according to a reinforcement learning algorithm. At a sufficient level of
activity, a node may become permanent. Otherwise, it may fade away and eventually be
deleted from the tree view.
The third feature of ConsensUs that will truly allow a global scaling of its use is that the
system is designed to operate on a peer-to-peer (P2P) architecture. This step allows us to
produce world-wide conversations that do not need expensive server farms to support a
large number of users. We have investigated the feasibility of deploying ConsensUs on
the Sun Microsystems JXTA P2P platform. It appears that such an environment would
allow large numbers of users to participate in a global-scale discourse while not requiring
any organization to install special servers. This has a certain sense of democratizing the
Internet.
The ConsensUs project seeks funding to support faculty, graduate, and undergraduate
students in building an initial Web-based proof of concept and, later, a JXTA
implementation. We have faculty expertise in Web and P2P development, social
computing and computational intelligence. Some preliminary work has been done to
show the overall feasibility of the project. Eventually we plan to introduce the base code
into the open source community for further development. The budget estimates for the
prototype is $100,000 and for the P2P implementation another $50,000.