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Title: Data Science for Public Policy: Of the people, for the people, by the people 2.0 ?

In this paper, we explore the role of data science in the public policy lifecycle. We posit policy documents (bills, acts, regulations and directives) as forms of social objects and present a methodology to understand interactions between prior context in professional and personal social networks to a given public policy document release. We employ natural language processing tools along with recent advances in semantic reasoning to formulate document-level proximity metrics which we use to predict the relevance (and impact) of the policy artifacts. These metrics serve as a measure of excitation between people and the public policy initiatives.
Authors:
 [1] ;  [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
OSTI Identifier:
1156759
DOE Contract Number:
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: ACM SIG Knowledge Discovery and Data Mining : Workshop on Data Science for Social Good,20140824, 20140827, New York City, NY, NY, USA,
Research Org:
Oak Ridge National Laboratory (ORNL)
Sponsoring Org:
USDOE; ORNL LDRD Director's R&D
Country of Publication:
United States
Language:
English
Subject:
semantic reasoning