This project will examine whether federal agency rulemaking can be
improved with two innovations: a) multi-level deliberation (MLD), in
which people discuss rulemakings in small groups that then select
members to represent the group in a higher-level group and b) the
combination of language technologies into an artificial discussion
facilitation agent (DiFA).
The social science herein breaks new ground in the nascent fields of
e-rulemaking and democratic deliberation research. The project will
advance research on measuring the quality of deliberation and the
effects of deliberation and DiFA on individuals and communities.
Research will involve four rulemaking experiments. The first three
are subsets of the final one. The final 3X2 experiment crosses MLD,
non-MLD deliberation, and non-deliberation with the presence or
absence of DiFA. The success of the various conditions of these
experiments will be measured using a multi-trait, multi-method
approach that will include survey and focus group measures of agency
official and participant perceptions and evaluations, a content
analysis measure of the cognitive sophistication of rulemaking
comments, both human-coded and automated content analyses of the
quality of deliberation, measures of the impact of the deliberations
on participants (knowledge, trust, citizenship), DiFA usage patterns,
and continued participation in our user community.
The project poses computer science challenges of combining several
Natural Language Processing technologies (primarily Interactive QA,
Dialogue Analysis, and Summarization) into a viable facilitation agent
and in applying these technologies in an eclectic, multi-user
discussion environment. We expect advances to be made within each
component technology. For example, we hope to increase the utility of
Dialogue Act tagging across applications and domains by using a set of
general discussion tags for tracking and summarizing threads of
discussion by combining dialogue structure and content analysis. We
will also investigate how general our Question Answer approaches are.
Key Personal:
Peter Muhlberger (Texas Tech University)
Nick Webb (ILS, UAlbany)
Jennifer Stromer-Galley (Department of Communication, UAlbany) Phone number: 518-442-4873