Multidimensional text analysis for eRulemaking

ABSTRACT

To support rule-writers, we are developing techniques to automatically analyze large number of public comments on proposed regulations. A document is analyzed in various ways including argument structure, topics, and opinions. The individual results are integrated into a unified output. The experiments reported here were performed on comments submitted to the Environmental Protection Agency in response to their proposed rule for mercury regulation.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.7 Natural Language Processing

General Terms:
Algorithms, Experimentation, Human Factors, Languages

Keywords:
argument structure, electronic rulemaking, federal government, regulations, semantic frame, text annotation