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Tracking and predicting growth areas in science
We explore the possibility of using co-citation clusters over three time periods to track the emergence and growth of research areas, and predict their near term change. Data sets are from three overlapping six-year periods: 1996-2001, 1997-2002 and 1998-2003. The methodologies of co-citation cluste...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Netherlands
2013
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7088887/ https://www.ncbi.nlm.nih.gov/pubmed/32214554 http://dx.doi.org/10.1007/s11192-006-0132-y |
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author | Small, Henry |
author_facet | Small, Henry |
author_sort | Small, Henry |
collection | PubMed |
description | We explore the possibility of using co-citation clusters over three time periods to track the emergence and growth of research areas, and predict their near term change. Data sets are from three overlapping six-year periods: 1996-2001, 1997-2002 and 1998-2003. The methodologies of co-citation clustering, mapping, and string formation are reviewed, and a measure of cluster currency is defined as the average age of highly cited papers relative to the year span of the data set. An association is found between the currency variable in a prior period and the percentage change in cluster size and citation frequency in the following period. The conflating factor of “single-issue clusters” is discussed and dealt with using a new metric called in-group citation. |
format | Online Article Text |
id | pubmed-7088887 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-70888872020-03-23 Tracking and predicting growth areas in science Small, Henry Scientometrics Article We explore the possibility of using co-citation clusters over three time periods to track the emergence and growth of research areas, and predict their near term change. Data sets are from three overlapping six-year periods: 1996-2001, 1997-2002 and 1998-2003. The methodologies of co-citation clustering, mapping, and string formation are reviewed, and a measure of cluster currency is defined as the average age of highly cited papers relative to the year span of the data set. An association is found between the currency variable in a prior period and the percentage change in cluster size and citation frequency in the following period. The conflating factor of “single-issue clusters” is discussed and dealt with using a new metric called in-group citation. Springer Netherlands 2013-06-20 2006 /pmc/articles/PMC7088887/ /pubmed/32214554 http://dx.doi.org/10.1007/s11192-006-0132-y Text en © Springer-Verlag/Akadémiai Kiadó 2006 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Small, Henry Tracking and predicting growth areas in science |
title | Tracking and predicting growth areas in science |
title_full | Tracking and predicting growth areas in science |
title_fullStr | Tracking and predicting growth areas in science |
title_full_unstemmed | Tracking and predicting growth areas in science |
title_short | Tracking and predicting growth areas in science |
title_sort | tracking and predicting growth areas in science |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7088887/ https://www.ncbi.nlm.nih.gov/pubmed/32214554 http://dx.doi.org/10.1007/s11192-006-0132-y |
work_keys_str_mv | AT smallhenry trackingandpredictinggrowthareasinscience |