Computational stylometry: predicting the authorship of investment arbitration awards

dc.contributor.author	Daniel Behn	*
dc.contributor.author	Runar Lie	*
dc.contributor.author	Malcolm Langford	*
dc.date.accessioned	2021-02-12T10:16:44Z
dc.date.available	2021-02-12T10:16:44Z
dc.date.issued	2020	*
dc.date.submitted	2021-01-04 11:59:56	*
dc.identifier	51234	*
dc.identifier.uri	https://directory.doabooks.org/handle/20.500.12854/63285
dc.description.abstract	Featuring contributions from a diverse set of experts, this thought-provoking book offers a visionary introduction to the computational turn in law and the resulting emergence of the computational legal studies field. It explores how computational data creation, collection, and analysis techniques are transforming the way in which we comprehend and study the law, and the implications that this has for the future of legal studies.	*
dc.language	English	*
dc.subject	K1-7720	*
dc.subject.classification	bic Book Industry Communication::L Law	en_US
dc.subject.other	legal research	*
dc.subject.other	empirical legal research	*
dc.subject.other	law and economics	*
dc.subject.other	computational law book	*
dc.subject.other	computational legal studies	*
dc.subject.other	computational social science	*
dc.title	Computational stylometry: predicting the authorship of investment arbitration awards	*
dc.type	chapter
oapen.identifier.doi	10.4337/9781788977456.00008	*
oapen.relation.isPublishedBy	01ceac28-75b4-492a-8eec-f9b98bc6b28c	*
oapen.relation.isPartOfBook	9781788977449	*
oapen.relation.isPartOfBook	9781788977456	*

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