Measuring novelty in science with word embedding.

Novelty is a core value in science, and a reliable measurement of novelty is crucial. This study proposes a new approach of measuring the novelty of scientific articles based on both citation data and text data. The proposed approach considers an article to be novel if it cites a combination of sema...

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Autores principales:	Sotaro Shibayama, Deyun Yin, Kuniko Matsumoto
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ea3c2b53cfd14a0190842d043d8f2ef2
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spelling	oai:doaj.org-article:ea3c2b53cfd14a0190842d043d8f2ef22021-12-02T20:09:40ZMeasuring novelty in science with word embedding.1932-620310.1371/journal.pone.0254034https://doaj.org/article/ea3c2b53cfd14a0190842d043d8f2ef22021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0254034https://doaj.org/toc/1932-6203Novelty is a core value in science, and a reliable measurement of novelty is crucial. This study proposes a new approach of measuring the novelty of scientific articles based on both citation data and text data. The proposed approach considers an article to be novel if it cites a combination of semantically distant references. To this end, we first assign a word embedding-a vector representation of each vocabulary-to each cited reference on the basis of text information included in the reference. With these vectors, a distance between every pair of references is computed. Finally, the novelty of a focal document is evaluated by summarizing the distances between all references. The approach draws on limited text information (the titles of references) and publicly shared library for word embeddings, which minimizes the requirement of data access and computational cost. We share the code, with which one can compute the novelty score of a document of interest only by having the focal document's reference list. We validate the proposed measure through three exercises. First, we confirm that word embeddings can be used to quantify semantic distances between documents by comparing with an established bibliometric distance measure. Second, we confirm the criterion-related validity of the proposed novelty measure with self-reported novelty scores collected from a questionnaire survey. Finally, as novelty is known to be correlated with future citation impact, we confirm that the proposed measure can predict future citation.Sotaro ShibayamaDeyun YinKuniko MatsumotoPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 7, p e0254034 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Sotaro Shibayama Deyun Yin Kuniko Matsumoto Measuring novelty in science with word embedding.
description	Novelty is a core value in science, and a reliable measurement of novelty is crucial. This study proposes a new approach of measuring the novelty of scientific articles based on both citation data and text data. The proposed approach considers an article to be novel if it cites a combination of semantically distant references. To this end, we first assign a word embedding-a vector representation of each vocabulary-to each cited reference on the basis of text information included in the reference. With these vectors, a distance between every pair of references is computed. Finally, the novelty of a focal document is evaluated by summarizing the distances between all references. The approach draws on limited text information (the titles of references) and publicly shared library for word embeddings, which minimizes the requirement of data access and computational cost. We share the code, with which one can compute the novelty score of a document of interest only by having the focal document's reference list. We validate the proposed measure through three exercises. First, we confirm that word embeddings can be used to quantify semantic distances between documents by comparing with an established bibliometric distance measure. Second, we confirm the criterion-related validity of the proposed novelty measure with self-reported novelty scores collected from a questionnaire survey. Finally, as novelty is known to be correlated with future citation impact, we confirm that the proposed measure can predict future citation.
format	article
author	Sotaro Shibayama Deyun Yin Kuniko Matsumoto
author_facet	Sotaro Shibayama Deyun Yin Kuniko Matsumoto
author_sort	Sotaro Shibayama
title	Measuring novelty in science with word embedding.
title_short	Measuring novelty in science with word embedding.
title_full	Measuring novelty in science with word embedding.
title_fullStr	Measuring novelty in science with word embedding.
title_full_unstemmed	Measuring novelty in science with word embedding.
title_sort	measuring novelty in science with word embedding.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/ea3c2b53cfd14a0190842d043d8f2ef2
work_keys_str_mv	AT sotaroshibayama measuringnoveltyinsciencewithwordembedding AT deyunyin measuringnoveltyinsciencewithwordembedding AT kunikomatsumoto measuringnoveltyinsciencewithwordembedding
_version_	1718375096571133952

Measuring novelty in science with word embedding.

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