This article compares the Faculty of 1000 (F1000) quality filtering results and Mendeley usage data with traditional bibliometric indicators, using a sample of 1397 Genomics and Genetics articles published in 2008 selected by F1000 Faculty Members (FMs). Both Mendeley user counts and F1000 article factors (FFas) correlate significantly with citation counts and associated Journal Impact Factors. However, the correlations for Mendeley user counts are much larger than those for FFas. It may be that F1000 is good at disclosing the merit of an article from an expert practitioner point of view while Mendeley user counts may be more closely related to traditional citation impact. Articles that attract exceptionally many citations are generally disorder or disease related, while those with extremely high social bookmark user counts are mainly historical or introductory.
Description
CiteULike: F1000, Mendeley and Traditional Bibliometric Indicators
%0 Conference Paper
%1 li2012f1000
%A Li, Xuemei
%A Thelwall, Mike
%D 2012
%E Archambault, Y. Gingras
%E Lariviere, V.
%J The 17th International Conference on Science and Technology Indicators
%K bibliometrics f1000 mendeley thelwall
%P 541--551
%T F1000, Mendeley and Traditional Bibliometric Indicators
%U http://sticonference.org/Proceedings/vol2/Li\_F1000\_541.pdf
%X This article compares the Faculty of 1000 (F1000) quality filtering results and Mendeley usage data with traditional bibliometric indicators, using a sample of 1397 Genomics and Genetics articles published in 2008 selected by F1000 Faculty Members (FMs). Both Mendeley user counts and F1000 article factors (FFas) correlate significantly with citation counts and associated Journal Impact Factors. However, the correlations for Mendeley user counts are much larger than those for FFas. It may be that F1000 is good at disclosing the merit of an article from an expert practitioner point of view while Mendeley user counts may be more closely related to traditional citation impact. Articles that attract exceptionally many citations are generally disorder or disease related, while those with extremely high social bookmark user counts are mainly historical or introductory.
@inproceedings{li2012f1000,
abstract = {This article compares the Faculty of 1000 (F1000) quality filtering results and Mendeley usage data with traditional bibliometric indicators, using a sample of 1397 Genomics and Genetics articles published in 2008 selected by F1000 Faculty Members ({FMs}). Both Mendeley user counts and F1000 article factors ({FFas}) correlate significantly with citation counts and associated Journal Impact Factors. However, the correlations for Mendeley user counts are much larger than those for {FFas}. It may be that F1000 is good at disclosing the merit of an article from an expert practitioner point of view while Mendeley user counts may be more closely related to traditional citation impact. Articles that attract exceptionally many citations are generally disorder or disease related, while those with extremely high social bookmark user counts are mainly historical or introductory.},
added-at = {2015-07-30T17:07:10.000+0200},
author = {Li, Xuemei and Thelwall, Mike},
biburl = {https://www.bibsonomy.org/bibtex/2694fd443d34932c6ed73fcbf5b35920f/sdo},
citeulike-article-id = {11689323},
citeulike-linkout-0 = {http://sticonference.org/Proceedings/vol2/Li\_F1000\_541.pdf},
description = {CiteULike: F1000, Mendeley and Traditional Bibliometric Indicators},
editor = {Archambault, Y. Gingras and Lariviere, V.},
interhash = {612e34d48054f77a05023c3fb6ea685a},
intrahash = {694fd443d34932c6ed73fcbf5b35920f},
journal = {The 17th International Conference on Science and Technology Indicators},
keywords = {bibliometrics f1000 mendeley thelwall},
pages = {541--551},
posted-at = {2012-11-14 16:38:10},
priority = {2},
timestamp = {2015-07-30T17:07:10.000+0200},
title = {F1000, Mendeley and Traditional Bibliometric Indicators},
url = {http://sticonference.org/Proceedings/vol2/Li\_F1000\_541.pdf},
year = 2012
}