About: Text as data: a machine learning-based approach to measuring uncertainty

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Text as data: a machine learning-based approach to measuring uncertainty
Creator	Nyman, Rickard Ormerod, Paul
source	ArXiv
abstract	The Economic Policy Uncertainty index had gained considerable traction with both academics and policy practitioners. Here, we analyse news feed data to construct a simple, general measure of uncertainty in the United States using a highly cited machine learning methodology. Over the period January 1996 through May 2020, we show that the series unequivocally Granger-causes the EPU and there is no Granger-causality in the reverse direction
has issue date	2020-06-11(xsd:dateTime)
has license	arxiv
sha1sum (hex)	04f90c6b1a9a0c30fe1661312e1f43ea2de8252f
resource representing a document's title	Text as data: a machine learning-based approach to measuring uncertainty
resource representing a document's body	covid:04f90c6b1a9a0c30fe1661312e1f43ea2de8252f#body_text
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