A Corpus of eRulemaking User Comments for Measuring Evaluability of Arguments

Joonsuk Park, Claire Cardie

Abstract:

eRulemaking is a means for government agencies to directly reach citizens to solicit their opinions and experiences regarding newly
proposed rules. The effort, however, is partly hampered by citizens’ comments that lack reasoning and evidence, which are largely
ignored since government agencies are unable to evaluate the validity and strength. We present Cornell eRulemaking Corpus – CDCP,
an argument mining corpus annotated with argumentative structure information capturing the evaluability of arguments. The corpus
consists of 731 user comments on Consumer Debt Collection Practices (CDCP) rule by the Consumer Financial Protection Bureau
(CFPB); the resulting dataset contains 4931 elementary unit and 1221 support relation annotations. It is a resource for building argument
mining systems that can not only extract arguments from unstructured text, but also identify what additional information is necessary
for readers to understand and evaluate a given argument. Immediate applications include providing real-time feedback to commenters,
specifying which types of support for which propositions can be added to construct better-formed argument